{"as_of":"2026-08-11T11:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5ff78c77db2a724e4aafc88dd68ca2c1d9068c79e43c931360348bd1e30696da","coverage":[{"denominator":73,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":73,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-08T22:06:55.065652Z","state":"measured"},{"denominator":73,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":73,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.05880/citation-record","integrity":"/paper/2607.05880/integrity","json":"/paper/2607.05880/citation-record.json","paper":"/paper/2607.05880"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.12208","last_updated":"2024-12-18T20:56:18Z","snapshot_observed_at":"2026-08-07T08:31:58.372526Z","submitted_at":"2024-01-22T18:51:07Z","title":"A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation","version":2},"cited_work":{"arxiv_id":"2401.12208","doi":"10.48550/arxiv.2401.12208","metadata_source":"pith","pith_arxiv_id":"2401.12208","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A vision- language foundation model to enhance efficiency of chest x-ray interpretation","venue":"cs.CV","work_id":"91ab4cd1-413f-4e31-be3f-78e309d19006","year":2024},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2401.12208","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:b3756f011d4ae78c4861c0366ffa2103a0f88d85b9362323f3f2fe49eabd353d","observation_id":"0dfa0d70-9a3b-4d06-a255-4e925f77f650","resolution":{"observed_at":"2026-07-08T22:15:39.397153Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.929681Z","title":"Advances in Neural Information Processing Systems (NeurIPS) , year =","venue":null,"work_id":"cf72f510-873d-4d90-aa55-d53542ef21bf","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:d14a6876d1d360f2715c79a4fbea2508687a3299fdcc47d5290b60b19136b9aa","observation_id":"89cb642e-f1e0-47b7-9786-d4ebf04ed2db","resolution":{"observed_at":"2026-07-08T22:15:39.931061Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.936254Z","title":"International Conference on Machine Learning (ICML) , year =","venue":null,"work_id":"de9fc420-f027-4d75-b156-cb6b8859fcd7","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:06f710d981626751cbefd55973e29354884a3b4323666085076c7df4e277cfd0","observation_id":"06b6205a-f07e-456e-adcf-c1e39f92f4f6","resolution":{"observed_at":"2026-07-08T22:15:39.937845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.924790Z","title":"International Conference on Learning Representations (ICLR) , year =","venue":null,"work_id":"f8d517d8-667f-45d3-ba6f-e555df946d37","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:8624d866cfc19bc581122ba09522424405b1ae8f4b1ca2a1be52a66386655d81","observation_id":"bfff7fc2-6496-4e2b-862f-dec94feb91c6","resolution":{"observed_at":"2026-07-08T22:15:39.927171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.948410Z","title":"and others , title =","venue":null,"work_id":"300f09e1-e44a-4f0b-b4eb-c9dcc59ce4c5","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:88665919fd3a489a51f4ebcec8500ea7165b4d0ed0ef311eed84a790fcde1ab5","observation_id":"d3fc8f0e-80b9-4147-9f6c-f05ab71aa7b2","resolution":{"observed_at":"2026-07-08T22:15:39.950424Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.911587Z","title":"Annual Meeting of the Association for Computational Linguistics (ACL) , year =","venue":null,"work_id":"c47b2089-b0ec-42ef-8329-d0e5d4f95567","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:32a8543e559c6060f226e33070373ebdc430278ef23b5059be5600172c8d7d75","observation_id":"66b421d6-6d39-444b-a0e8-c79113a9cc83","resolution":{"observed_at":"2026-07-08T22:15:39.912893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.919807Z","title":"Conference on Computer Vision and Pattern Recognition (CVPR) , year =","venue":null,"work_id":"a9cfa902-28b5-415e-bcdc-9940c8f18b5f","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:5c9f80de2470bf13a8c8dfc1f3916089284c483265f6c093b26b38547c96c80c","observation_id":"eea0c4d7-8b11-4db0-a8e1-0d094573d2bb","resolution":{"observed_at":"2026-07-08T22:15:39.922072Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.938744Z","title":"International Conference on Learning Representations (ICLR) , year =","venue":null,"work_id":"7918f39d-3fce-4528-9b10-762064f51e29","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:0342c13df1a88a9fcd8c6e02594ad8c9dceb20139fd0e772b1a0993fdd9ee855","observation_id":"06195529-173f-4ff9-9172-6c13333be020","resolution":{"observed_at":"2026-07-08T22:15:39.940047Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2603.05498","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.373784Z","title":"arXiv preprint arXiv:2603.05498 , year=","venue":null,"work_id":"d56acd62-b465-4036-8644-f69bd935b2cd","year":2026},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:fd859ca6fd7ff0b368942b236e07726d8c5477685abc245e8fb44e5e2d0260a4","observation_id":"f9ac20ad-5df6-4508-9d41-1c5e7deb4ee1","resolution":{"observed_at":"2026-07-08T22:15:39.375746Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.899399Z","title":"NeurIPS Datasets and Benchmarks , year =","venue":null,"work_id":"a67177ab-45a6-494b-80bf-b7e2073b09b4","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:5af4e4c74868b47681e28eab24d5860eb971e34de3b8c09915dc194f81f733d9","observation_id":"8a9ebd76-239c-433a-9f86-c0db37b18755","resolution":{"observed_at":"2026-07-08T22:15:39.900866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.901434Z","title":"Findings of the Association for Computational Linguistics (ACL) , year =","venue":null,"work_id":"d51748c2-b7f6-4a0a-8d8f-70d401ef7d49","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:2f558d61ae1a0bbf722ebeb8646d67c05df76a380f390a6558c23f7fd2030a7b","observation_id":"4c98ce13-603f-4b91-b61a-9cb80bfbab0e","resolution":{"observed_at":"2026-07-08T22:15:39.902868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15594","last_updated":"2025-10-19T10:32:43Z","snapshot_observed_at":"2026-08-02T10:23:50.881300Z","submitted_at":"2024-11-23T16:03:35Z","title":"A Survey on LLM-as-a-Judge","version":6},"cited_work":{"arxiv_id":"2411.15594","doi":"10.1016/j.xinn.2025.101253","metadata_source":"pith","pith_arxiv_id":"2411.15594","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Survey on LLM-as-a-Judge","venue":"cs.CL","work_id":"2676656a-67bd-4ad5-bad6-cb6f5fcdbfbe","year":2024},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2411.15594","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:f0963094c40e58f73cb5f82f20d91b112b40a64029f78a7cbd842f7c5e529c6e","observation_id":"bb19bb60-170e-454d-9887-472ee1aab0d3","resolution":{"observed_at":"2026-07-08T22:15:39.427002Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-07-10T18:20:01.818871+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-10T18:20:01.818871+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.929916Z","title":"Conference on Empirical Methods in Natural Language Processing (EMNLP) , year =","venue":null,"work_id":"d8227af2-8c8b-433d-8ca3-8b767a9f121b","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:2ac4769fd4ed4222b0d520bdebdaf922e4498e40011934a1a2d33c4b17f0bc34","observation_id":"aa771372-794a-4d3f-aea3-a5cdced679d7","resolution":{"observed_at":"2026-07-08T22:15:39.931247Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.895340Z","title":"Text Summarization Branches Out, ACL Workshop , year =","venue":null,"work_id":"eba47864-ecac-4894-908c-d6859f8f04bc","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:cdfe43e3e3ade716f4d5050524fad72536831174cb46c84519f2b06bb6c4b5a7","observation_id":"ec5c8d11-c20c-4131-adf3-34c1eb083b24","resolution":{"observed_at":"2026-07-08T22:15:39.896713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.888973Z","title":"Annual Meeting of the Association for Computational Linguistics (ACL) , year =","venue":null,"work_id":"15c24480-ae62-448b-9f2f-88711fc3ba00","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:766446b3ecdfa502e9d03786f44a7ad8750b66a215343155d3b6c79469d68fb5","observation_id":"3027343b-a002-4833-9658-c19d3c59af15","resolution":{"observed_at":"2026-07-08T22:15:39.890420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.945903Z","title":"Patterns , year =","venue":null,"work_id":"edb58cf6-ae08-4e88-b0ba-b24144e96522","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:aedf8215d9d3975a9e6e1801b9de82644b6247c1deb783266e6deb9514fdb26d","observation_id":"e778d5c4-e85d-4009-98b1-9d64b01bf57f","resolution":{"observed_at":"2026-07-08T22:15:39.947519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.00228","last_updated":"2025-05-10T13:56:11Z","snapshot_observed_at":"2026-08-07T15:57:30.073877Z","submitted_at":"2025-05-01T00:29:50Z","title":"ReXGradient-160K: A Large-Scale Publicly Available Dataset of Chest Radiographs with Free-text Reports","version":2},"cited_work":{"arxiv_id":"2505.00228","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.00228","snapshot_observed_at":"2026-07-08T22:15:39.405585Z","title":"Rexgradient-160k: A large-scale publicly available dataset of chest radiographs with free-text reports","venue":"eess.IV","work_id":"f61477dc-52c2-43a1-8e38-06993fbb2da9","year":2025},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2505.00228","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:32149102a681e9fb7040bf88643eb81c4ee4947a47fc027d3e36ebc9e98446ea","observation_id":"27a4f072-0cc2-46a5-8a8e-506039acacf4","resolution":{"observed_at":"2026-07-08T22:15:39.407072Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.00890","last_updated":"2023-06-01T16:50:07Z","snapshot_observed_at":"2026-08-09T05:23:28.778360Z","submitted_at":"2023-06-01T16:50:07Z","title":"LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day","version":1},"cited_work":{"arxiv_id":"2306.00890","doi":"10.48550/arxiv.2306.00890","metadata_source":"pith","pith_arxiv_id":"2306.00890","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day","venue":"cs.CV","work_id":"19dcd63e-57db-4bc7-83cb-d96d41270f55","year":2023},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2306.00890","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:f30214761433917413331fd3083a2c512faaff0c62dfdea5ecde7bd344cb303b","observation_id":"4e14b573-c90e-432c-816f-0978d4f88856","resolution":{"observed_at":"2026-07-08T22:15:39.400235Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-05-25T22:53:39.586163+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T22:53:39.586163+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.05201","last_updated":"2026-04-06T19:50:20Z","snapshot_observed_at":"2026-08-07T23:53:34.814339Z","submitted_at":"2025-07-07T17:01:44Z","title":"MedGemma Technical Report","version":4},"cited_work":{"arxiv_id":"2507.05201","doi":"10.48550/arxiv.2507.05201","metadata_source":"pith","pith_arxiv_id":"2507.05201","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"MedGemma Technical Report","venue":"cs.AI","work_id":"3d3f25c0-31e8-4859-bb3d-0d719b47a63d","year":2025},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2507.05201","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:ace25b3e41069150884671ef0cce2cf70b51cec4376052a0ba15778db4c99b50","observation_id":"6f0576f2-c0ad-416b-9ea6-6900eb67a717","resolution":{"observed_at":"2026-07-08T22:15:39.426841Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.938520Z","title":", title =","venue":null,"work_id":"cf6dbd69-3bfe-47be-b324-6184d89dbdf9","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:2f637689da0356ef90e8a4a6150e8e9cc94c79cd3f2a9dadee5c23d665ca2d73","observation_id":"3f309358-6d69-4a95-bcd4-014b9710c7fb","resolution":{"observed_at":"2026-07-08T22:15:39.940268Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2604.00493","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.388667Z","title":"arXiv preprint arXiv:2604.00493 , year =","venue":null,"work_id":"8ac9bc6a-153c-46db-bacc-1d729da61bf7","year":2026},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:d9c1b35859231707a123bff859baa2b0ee89888275f4ffa078b7795aacf457ab","observation_id":"02ad41e0-7f8a-4756-b8eb-8767088bfac0","resolution":{"observed_at":"2026-07-08T22:15:39.390814Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.951132Z","title":"ICLR Workshop , year =","venue":null,"work_id":"3fd6a58c-6b9b-45e9-af1e-95ea85ed4b2a","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:457b7d3505b72853b7301602a5fbfe38099ee74f1a75de9d50f186386436b40f","observation_id":"e88ac6c1-09d2-4db0-9787-5292db2dc5ca","resolution":{"observed_at":"2026-07-08T22:15:39.952540Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06824","last_updated":"2024-08-19T01:18:41Z","snapshot_observed_at":"2026-07-06T16:30:37.867641Z","submitted_at":"2023-10-10T17:54:39Z","title":"The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets","version":3},"cited_work":{"arxiv_id":"2310.06824","doi":"10.18653/v1/2025.findings-acl.38","metadata_source":"pith","pith_arxiv_id":"2310.06824","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets","venue":"cs.AI","work_id":"400e017f-8643-4166-b6da-a75d4446da80","year":2023},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2310.06824","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:e28d95ceb6b4e4dd126fe6e45ef59b2ea3d922b508e36f1caeb850b8cabc33da","observation_id":"4bac72dc-03ce-441b-9349-00aae98d8dad","resolution":{"observed_at":"2026-07-08T22:15:39.418340Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.10248","last_updated":"2024-10-10T13:20:13Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-08-20T12:21:05Z","title":"Steering Language Models With Activation Engineering","version":5},"cited_work":{"arxiv_id":"2308.10248","doi":"10.18653/v1/2024.findings-acl.611","metadata_source":"pith","pith_arxiv_id":"2308.10248","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Steering Language Models With Activation Engineering","venue":"cs.CL","work_id":"d525fe06-5560-4e97-86fc-7a0e551f5b17","year":2023},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2308.10248","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:9a444ff0c38626153f6c62d5e0ad7540decf5c770570ffd72fe8bbfc2347a9cb","observation_id":"281ad1e6-808c-47c4-8c5e-ad9950964326","resolution":{"observed_at":"2026-07-08T22:15:39.367435Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.955580Z","title":"Advances in Neural Information Processing Systems (NeurIPS) , year =","venue":null,"work_id":"2664030a-2711-4555-9b69-9938ecef7562","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:8bac1d454dab61fa54b833ca0234f7277c607f9749cabf1787fafd67ecf28ce3","observation_id":"89824c50-ae2b-4b90-8377-b2e5b036a606","resolution":{"observed_at":"2026-07-08T22:15:39.957363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.909995Z","title":"Annual Meeting of the Association for Computational Linguistics (ACL) , year =","venue":null,"work_id":"a5537d90-f504-4b09-bb86-79db866187a5","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:496e4ffa77b36c61242eb02d506a7fa4ddf7923c5100777cbdcb7017950e68de","observation_id":"d5125081-9e02-4857-9eb2-54e3e68610e0","resolution":{"observed_at":"2026-07-08T22:15:39.911269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.905914Z","title":", title =","venue":null,"work_id":"1bf5204d-0ecc-413a-9de7-ca25b51bb966","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:f3f871e367d09afd219b011b38982cfd12ab288eda73054cda4b4ed2b97d462e","observation_id":"be53d510-a96e-4373-9d2f-13a223163bcc","resolution":{"observed_at":"2026-07-08T22:15:39.907438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.944835Z","title":"Conference on Empirical Methods in Natural Language Processing (EMNLP) , year =","venue":null,"work_id":"8b71140b-e913-406e-8c87-3f7f27cfaad8","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:7182425d3ce522f9a19c674a2bf3b6a8d746479c60ac026375418df2295072d6","observation_id":"3fba6dbc-2862-4215-9ea9-1e97ac36d51b","resolution":{"observed_at":"2026-07-08T22:15:39.946107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.903829Z","title":"International Conference on Learning Representations (ICLR) , year =","venue":null,"work_id":"5f0439a9-be91-4ada-9085-970f3f1fe893","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:904701a06ab1951128ecdeffe60d2ca249bced2945387c85e400733ad219bba3","observation_id":"22cfbd89-2492-48d6-8573-32d3b1edb53c","resolution":{"observed_at":"2026-07-08T22:15:39.905306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.05221","last_updated":"2022-11-21T16:38:35Z","snapshot_observed_at":"2026-08-06T08:34:11.887259Z","submitted_at":"2022-07-11T22:59:39Z","title":"Language Models (Mostly) Know What They Know","version":4},"cited_work":{"arxiv_id":"2207.05221","doi":"10.1145/3618260.3649777","metadata_source":"pith","pith_arxiv_id":"2207.05221","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Models (Mostly) Know What They Know","venue":"cs.CL","work_id":"8ca58a10-da41-4f70-baae-7e449512e345","year":2022},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2207.05221","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:91dde25d82d93e02596bb792b4939e4d5fcc97f84a2d67f69ec8ac8ef312a696","observation_id":"f3a6dac5-cb22-4ee5-bb29-9f9d34bd05b9","resolution":{"observed_at":"2026-07-08T22:15:39.421156Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-05-21T07:53:13.382372+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-21T07:53:13.382372+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.895071Z","title":"International Conference on Machine Learning (ICML) , year =","venue":null,"work_id":"f9586ef9-b987-4b04-86c4-44cf175c3957","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:816a62728d081d1367d2c5012c1d6737ca4da5e51da83273c5cd417275168af0","observation_id":"0ec73c1c-8eb1-4c86-8c19-710324928cdc","resolution":{"observed_at":"2026-07-08T22:15:39.896891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.862231Z","title":"Scientific Data , year =","venue":null,"work_id":"a09662d4-8ce9-43cd-abcb-b91c99a43271","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:c8a6faf6d2084893bcfa0f61b061efa7f8fb67bfac82f8660d8e1db1e1cd864a","observation_id":"7297ded4-1184-41bd-b3b5-9c98d0edc34d","resolution":{"observed_at":"2026-07-08T22:15:39.863727Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.897437Z","title":"European Conference on Computer Vision (ECCV) , year =","venue":null,"work_id":"a94d6c6b-3852-43d3-ad2c-b1f2f3fa9383","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:30474d70b32a918d5bcac7f27b7d7bfafbac1c57cc2de36eca0d9a063248c5e7","observation_id":"15d0f7bc-44e1-4c4f-a6a1-c284967aeeb2","resolution":{"observed_at":"2026-07-08T22:15:39.899089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.927864Z","title":"and Nodine, Calvin F","venue":null,"work_id":"19d1f874-0c67-4442-b45f-824f9f490734","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:4b1e40777b252f960bbcaec155ed87afcc709ef5ea62cb2a8f6cd64accc15ecd","observation_id":"565a830d-a349-45e1-8ac6-92e8eae92eee","resolution":{"observed_at":"2026-07-08T22:15:39.929193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.888784Z","title":"2024 , url =","venue":null,"work_id":"4b27313b-ce02-44e2-bf47-58c09c5df1a7","year":2024},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:dfc366aaa928a8b8a484e09d841de2b9e0f00001640d31061ccb02581ce6ef1e","observation_id":"a81c5a23-d390-4998-9473-d90612fb9fea","resolution":{"observed_at":"2026-07-08T22:15:39.890130Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.890772Z","title":"Journal of the American College of Radiology , year =","venue":null,"work_id":"1ea172d2-9b33-47a2-b101-d45edbd0b534","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:111e1fe7f0434e13b76973a10435b11ccfc445e665cb0fb36b488eb3f9d69e44","observation_id":"a1eadd41-c79a-45d0-b5a5-316fb64a259c","resolution":{"observed_at":"2026-07-08T22:15:39.892286Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.893054Z","title":"and others , title =","venue":null,"work_id":"05493ed2-cde2-458b-b246-05fe1503fbb2","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:a04c319aae4505b599e88406d94f5a4318b588ef0ae23946e3cae4e5a2ddafff","observation_id":"b31ca313-bb48-4b89-8658-491621115696","resolution":{"observed_at":"2026-07-08T22:15:39.894456Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.899798Z","title":"Advances in Neural Information Processing Systems (NeurIPS) , year =","venue":null,"work_id":"5dd86c8e-5ae9-4d72-bfed-6011f54ef05d","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:aea1273e2dd74d18bc5eeec76f2e1a50e790f222dbb9ed19d4eefe284e9419ab","observation_id":"bb35eda8-c40c-41ed-9b17-bd732b438781","resolution":{"observed_at":"2026-07-08T22:15:39.901158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.911980Z","title":"International Conference on Learning Representations (ICLR) , year =","venue":null,"work_id":"075ef0bf-50b1-4706-ba81-f88cb82c722b","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:355764512e1ed68a738f293bf8c79eeac4cf4dbb9a8e466b28127498e521cbfb","observation_id":"303a47e0-6fa3-4efb-9618-51f3f8758035","resolution":{"observed_at":"2026-07-08T22:15:39.913350Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.884082Z","title":"International Conference on Machine Learning (ICML) , year =","venue":null,"work_id":"b8193031-b29a-44aa-a7b6-12481a848518","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:f274aff8d815e2e9fe2354a65226e8d5b8912248599016433ba6fba159a5a7c6","observation_id":"48b61e6d-ae35-4185-b921-3233dd0307c0","resolution":{"observed_at":"2026-07-08T22:15:39.885715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.882185Z","title":"Advances in Neural Information Processing Systems (NeurIPS) , year =","venue":null,"work_id":"6b3bf9d9-dc81-4d69-adde-0b1db35314e8","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:bab2342b0466f6fce67b132e2a7a5d66ad7334dc085168164ca2798e385fe358","observation_id":"efa93690-dc52-47a4-929b-49c122f5159f","resolution":{"observed_at":"2026-07-08T22:15:39.883886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":"2303.08774","doi":"10.1002/tea.20265","metadata_source":"pith","pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"GPT-4 Technical Report","venue":"cs.CL","work_id":"b928e041-6991-4c08-8c81-0359e4097c7b","year":2023},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:dd70e6526d35a77c71ca46b81202788f6a71c8b1844ed2f499912b2d5d74678e","observation_id":"44311491-93a7-449d-b3cf-b7165c8905a2","resolution":{"observed_at":"2026-07-08T22:15:39.412621Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.942931Z","title":"Nature Biomedical Engineering , volume =","venue":null,"work_id":"bae09c09-42d7-4d13-a08c-62890acb987b","year":2022},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:325ca36999bf7d33f2164caeb6dae4bc20be6d15b278bf62cf246e60ec704c2d","observation_id":"e40c91f3-ad38-4342-ac1c-c5e9307b03d8","resolution":{"observed_at":"2026-07-08T22:15:39.944168Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.00915","last_updated":"2025-01-08T22:58:51Z","snapshot_observed_at":"2026-07-06T14:57:39.647497Z","submitted_at":"2023-03-02T02:20:04Z","title":"BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs","version":3},"cited_work":{"arxiv_id":"2303.00915","doi":"10.48550/arxiv.2303.00915","metadata_source":"pith","pith_arxiv_id":"2303.00915","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs","venue":"cs.CV","work_id":"6fcf8750-00b8-4f3e-9f0b-965a879a5dff","year":2023},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2303.00915","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:7d71ea24649226112b98718c69bcb69a13298e40d1edcd6f9b8f4e4cf4bd898d","observation_id":"09b66c10-a11d-40a0-87d7-bb88b21f6d68","resolution":{"observed_at":"2026-07-08T22:15:39.409213Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-03T16:39:08.594818+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-03T16:39:08.594818+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.02463","last_updated":"2023-11-16T12:38:46Z","snapshot_observed_at":"2026-08-08T04:57:05.131540Z","submitted_at":"2023-08-04T17:00:38Z","title":"Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data","version":5},"cited_work":{"arxiv_id":"2308.02463","doi":"10.48550/arxiv.2308.02463","metadata_source":"pith","pith_arxiv_id":"2308.02463","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URL https://arxiv.org/abs/ 2308.02463","venue":"cs.CV","work_id":"095eccb0-a554-40a1-8b07-456e9181960c","year":2023},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2308.02463","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:cc869326dcf02640781c14dcd55193d8511c0ce9aee0d7685aa7dea87bc96ede","observation_id":"e2d0df3c-50b8-4f1d-b93c-f8b1b45c834c","resolution":{"observed_at":"2026-07-08T22:15:39.412447Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.01317","last_updated":"2023-09-07T23:07:51Z","snapshot_observed_at":"2026-08-07T10:06:27.699724Z","submitted_at":"2023-08-02T17:59:45Z","title":"ELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders","version":2},"cited_work":{"arxiv_id":"2308.01317","doi":null,"metadata_source":"pith","pith_arxiv_id":"2308.01317","snapshot_observed_at":"2026-07-08T22:15:39.393729Z","title":"arXiv preprint arXiv:2308.01317 , year=","venue":"cs.CV","work_id":"f27b3042-54a2-4d39-8a00-8ddb6f087375","year":2023},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2308.01317","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:cf76e62882b1fcc94823f5812436cdbe452722c17d2dc0db62110f338bc0021a","observation_id":"9e2ae5a2-b05f-480e-9901-b91c68d06028","resolution":{"observed_at":"2026-07-08T22:15:39.395307Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.13668","last_updated":"2024-04-26T16:29:54Z","snapshot_observed_at":"2026-08-10T05:46:39.741114Z","submitted_at":"2023-11-22T19:45:40Z","title":"MAIRA-1: A specialised large multimodal model for radiology report generation","version":3},"cited_work":{"arxiv_id":"2311.13668","doi":"10.48550/arxiv.2311.13668","metadata_source":"pith","pith_arxiv_id":"2311.13668","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"L.; Bannur, S.; Bouzid, K.; Castro, D","venue":"cs.CL","work_id":"ef50f610-9e4e-4d5b-8c85-35e180f09d5b","year":2023},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2311.13668","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:8eeadb1c99cd2978fdb66e0a26b46f4ad8067f12fdb63bb2cb858ba62dd170a7","observation_id":"513fc084-3a29-44e3-9d77-c7d52f83a6a0","resolution":{"observed_at":"2026-07-08T22:15:39.421549Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.04449","last_updated":"2024-09-20T17:17:43Z","snapshot_observed_at":"2026-07-06T18:26:46.402024Z","submitted_at":"2024-06-06T19:12:41Z","title":"MAIRA-2: Grounded Radiology Report Generation","version":2},"cited_work":{"arxiv_id":"2406.04449","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.04449","snapshot_observed_at":"2026-07-08T22:15:39.401613Z","title":"Maira-2: Grounded radiology report gener- ation","venue":"cs.CL","work_id":"02db650c-ab84-4eff-ba3b-c2e67535494d","year":2024},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2406.04449","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:989657575ace9a9b66bc67f6a39025012cdda359a70820a1c8c36100fa47d1b0","observation_id":"3f34c18a-890f-4c80-9d10-baad32289dbe","resolution":{"observed_at":"2026-07-08T22:15:39.403175Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.18416","last_updated":"2024-05-01T17:12:10Z","snapshot_observed_at":"2026-07-06T18:06:49.190172Z","submitted_at":"2024-04-29T04:11:28Z","title":"Capabilities of Gemini Models in Medicine","version":2},"cited_work":{"arxiv_id":"2404.18416","doi":"10.48550/arxiv.2404.18416","metadata_source":"pith","pith_arxiv_id":"2404.18416","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Capabilities of Gemini Models in Medicine","venue":"cs.AI","work_id":"27822395-fb36-4417-a4f3-f0a1f801ac20","year":2024},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2404.18416","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:d04c3f66b2bd9f4f89f1d7aa96372cfb41dbb91099c96be40431a00bb6da4716","observation_id":"c8fa48d6-2932-45fe-8458-11847955e976","resolution":{"observed_at":"2026-07-08T22:15:39.424264Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.03162","last_updated":"2024-05-06T04:44:22Z","snapshot_observed_at":"2026-07-06T18:10:12.621492Z","submitted_at":"2024-05-06T04:44:22Z","title":"Advancing Multimodal Medical Capabilities of Gemini","version":1},"cited_work":{"arxiv_id":"2405.03162","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.03162","snapshot_observed_at":"2026-07-08T22:15:39.414354Z","title":"Advancing multi- modal medical capabilities of gemini","venue":"cs.CV","work_id":"474dd269-b3b8-4646-97e9-1efc1cf6a60b","year":2024},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2405.03162","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:550bfe962e4b4c2962272ecfbb360a3e3576582194ff9cd103e3a1950906805c","observation_id":"f1604fd7-6ca0-4815-9d3e-3fbffc4eec72","resolution":{"observed_at":"2026-07-08T22:15:39.415921Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.886686Z","title":"Nature , year =","venue":null,"work_id":"01a76a23-14f3-4642-b5a9-6789d1145c06","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:76fa07a715706c7340b9eefdbef9b6694eadcea68fdf94ebb45eecd476c13cb6","observation_id":"4f875698-5093-4f3f-8183-65771a7991b4","resolution":{"observed_at":"2026-07-08T22:15:39.888084Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.891106Z","title":"2024 , url =","venue":null,"work_id":"15a0eda7-7c66-44c1-a158-ac1bb21180e0","year":2024},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:7ee68391c1e2dcec015950ffe0821fcda3822b7b906160c2fb78dee8edb7f943","observation_id":"81c0fdfa-efa6-4054-8b3f-be7bd5b45cbf","resolution":{"observed_at":"2026-07-08T22:15:39.892425Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.897320Z","title":"Annual Meeting of the Association for Computational Linguistics (ACL) , year =","venue":null,"work_id":"279736ce-7730-4d5d-8d7e-40798a0d9e5f","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:912a8ca4a73a6f7f05979c3cd403170087a4c11bd88c8ec8166277e5dccebc67","observation_id":"547b6f56-b663-45f3-95f1-c027cd01733b","resolution":{"observed_at":"2026-07-08T22:15:39.898769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.907840Z","title":"Conference on Computer Vision and Pattern Recognition (CVPR) , year =","venue":null,"work_id":"ad71e453-4adc-420d-b19b-40dc0718e491","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:c425219c6c38c45b2167b84d9932ae4ae3161baa51744ebee268ce4c11b077e9","observation_id":"1d1c4c2a-75de-4ea7-b866-d6bee922e164","resolution":{"observed_at":"2026-07-08T22:15:39.909053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.14786","last_updated":"2025-02-20T18:08:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-20T18:08:29Z","title":"SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features","version":1},"cited_work":{"arxiv_id":"2502.14786","doi":"10.48550/arxiv.2502.14786","metadata_source":"pith","pith_arxiv_id":"2502.14786","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features","venue":"cs.CV","work_id":"50eec732-2d41-432f-9dcf-ac7fff235ea5","year":2025},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2502.14786","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:7283f1a55fa8d90992d208a358e8feaded412bd7b029ce5f3299513344d06081","observation_id":"00359ee8-3003-4fc0-8cb7-c152841cd3ab","resolution":{"observed_at":"2026-07-08T22:15:39.415615Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-07-10T23:49:08.777694+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-10T23:49:08.777694+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.866750Z","title":"ACM Symposium on Operating Systems Principles (SOSP) , year =","venue":null,"work_id":"9a05917b-a54c-4701-ba29-26c8ef0f9f6a","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:d0774526d24fa6d3802600a1bd5181da65a1c4bedd862111e6aa883113de5729","observation_id":"aedd1ad0-3a17-4427-a43d-7b0d87a4c7f9","resolution":{"observed_at":"2026-07-08T22:15:39.868200Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12191","last_updated":"2024-10-03T15:54:49Z","snapshot_observed_at":"2026-08-06T05:35:29.109022Z","submitted_at":"2024-09-18T17:59:32Z","title":"Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution","version":2},"cited_work":{"arxiv_id":"2409.12191","doi":"10.48550/arxiv.2409.12191","metadata_source":"pith","pith_arxiv_id":"2409.12191","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution","venue":"cs.CV","work_id":"8abcfe4f-e0fb-44b7-9123-448fac95f90a","year":2024},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2409.12191","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:64da533451e0d1e989c8c4088564c5d64d6088596ec86a3f1a922cc1090f012d","observation_id":"d08394f2-cf4e-4f6e-ad11-4ced829474a9","resolution":{"observed_at":"2026-07-08T22:15:39.365716Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-07-11T02:19:33.884263+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T02:19:33.884263+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.07726","last_updated":"2024-10-10T17:28:23Z","snapshot_observed_at":"2026-08-08T07:16:45.596308Z","submitted_at":"2024-07-10T14:57:46Z","title":"PaliGemma: A versatile 3B VLM for transfer","version":2},"cited_work":{"arxiv_id":"2407.07726","doi":"10.48550/arxiv.2407.07726","metadata_source":"pith","pith_arxiv_id":"2407.07726","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"PaliGemma: A versatile 3B VLM for transfer","venue":"cs.CV","work_id":"df6f48b3-5792-47c7-9614-cb856ea31ad9","year":2024},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2407.07726","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:b9366fea053814f18060a36772086064301fff33e92233dd7bc0c064ff486fb9","observation_id":"c8aa7ec7-9204-4266-8093-872e58d440ae","resolution":{"observed_at":"2026-07-08T22:15:39.418865Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-05-22T13:22:31.538292+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T13:22:31.538292+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.868789Z","title":"American Journal of Roentgenology , year =","venue":null,"work_id":"037c1cbb-baa1-449f-bf09-df7a21efce81","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:798f65185b0095479ba51ae581ea79aa1aaf313b068554e71946b722bcf8ab7a","observation_id":"a2d17cc9-0177-49de-a797-704ef4a65595","resolution":{"observed_at":"2026-07-08T22:15:39.870234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.922817Z","title":null,"venue":null,"work_id":"01bbcf00-417e-479f-b5ef-6e83833a1116","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:9fc7e11f9383cefe8c516eeaae2801b894acae2662e45539f1677e2bed02213a","observation_id":"ee908cf4-7307-4ce0-ac3e-63dace68714a","resolution":{"observed_at":"2026-07-08T22:15:39.924041Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.903416Z","title":"2025 , url =","venue":null,"work_id":"7a2b7c40-8cbb-4e0c-abe7-8b6aa3848e6b","year":2025},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:b6d00d62f22762565ee5e6db671200ee76149bcb9eb25c543798f0c31b3202de","observation_id":"ebbe9f56-bfb3-42bb-bae2-9f20322b22da","resolution":{"observed_at":"2026-07-08T22:15:39.904740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.940697Z","title":"Radiology: Artificial Intelligence , volume =","venue":null,"work_id":"9145db40-4fa7-4a75-809b-d1cae6faf1a1","year":2020},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:6f173cf96093fed18ac430983f9feb1d90e418e8bb8b9a063cc5b12f802edb41","observation_id":"0b3cf891-357e-4a1b-9697-55e66b86fad2","resolution":{"observed_at":"2026-07-08T22:15:39.942244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.946795Z","title":"Machine Learning for Healthcare (MLHC), PMLR 106 , year =","venue":null,"work_id":"f79716b4-6b15-4c27-b4ea-ed502d2f074d","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:fdb507c1438eaaa671d54217d1046fcdb064b87ac3a961010e09ac69cc7c06ac","observation_id":"61d39124-7cdb-4fb9-a5e8-5f9f5f474984","resolution":{"observed_at":"2026-07-08T22:15:39.948109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.933866Z","title":"European Conference on Computer Vision (ECCV) , year =","venue":null,"work_id":"8eb085e8-99f9-430f-912e-daacfc1f4a15","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:aafb20ce3a8f48ccfadff28cd063d6fda49638b2f733f2c5020c8a1b8889fb8a","observation_id":"1866dd13-6185-4775-bbff-fe85b89d4e3d","resolution":{"observed_at":"2026-07-08T22:15:39.935440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T02:37:54.519855Z","title":null,"venue":null,"work_id":"72647878-5eae-4741-b770-5602b7561189","year":2026},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:9154485ad1ccf53ddfabc58f1e22d9882e4746715a31510d18c58d6038a5e90f","observation_id":"0eb5f197-c2f8-4981-8552-8a4a004ea6f3","resolution":{"observed_at":"2026-07-08T22:15:39.937642Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T19:27:32.561811Z","title":null,"venue":null,"work_id":"48a06fba-cfc0-4db3-9a8d-e2a4d8c69eb9","year":2025},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:2e26f85ea20651188faf5a348be8cee1b68aeed8a02372c6203196fee21ed0d0","observation_id":"82076906-5728-43e0-a5e5-8f43ef718495","resolution":{"observed_at":"2026-07-08T22:15:39.950165Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.940955Z","title":"2025 , howpublished =","venue":null,"work_id":"e85d5a4b-48d8-4345-915e-796eb1051327","year":2025},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:e31993dce0c6b9a703fa5a78ce0ec9215c017e4ade9b941b9bfa1b026763afdd","observation_id":"944de35d-0f88-42ce-b6c0-000e089cae32","resolution":{"observed_at":"2026-07-08T22:15:39.942709Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.958050Z","title":"Annual Meeting of the Association for Computational Linguistics (ACL) , year =","venue":null,"work_id":"c63279d9-ff98-4481-b7ad-afc9d64cccf3","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:b4c86ff329f2036897f034a1e4d988148e6f4d553f478fc4aa731105f4d51483","observation_id":"2efda317-6b2d-4f3b-b250-032cdb6b5d17","resolution":{"observed_at":"2026-07-08T22:15:39.959577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.927677Z","title":"Findings of the Association for Computational Linguistics (EMNLP) , year =","venue":null,"work_id":"d0d0aeb9-3c9c-491b-ba32-0b3525a87ff3","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:4b8cbad1fe5c02d66824c6b1bf865c1bd8a2582fc9ff8f25af6e3d95afafbb83","observation_id":"ed797503-c1d6-4da6-9548-859e7c23e0ce","resolution":{"observed_at":"2026-07-08T22:15:39.929021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.24001","last_updated":"2026-04-27T03:32:46Z","snapshot_observed_at":"2026-08-10T22:10:38.950199Z","submitted_at":"2026-04-27T03:32:46Z","title":"CT-FineBench: A Diagnostic Fidelity Benchmark for Fine-Grained Evaluation of CT Report Generation","version":1},"cited_work":{"arxiv_id":"2604.24001","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.24001","snapshot_observed_at":"2026-07-08T22:15:39.377383Z","title":"CT-FineBench: A Diagnostic Fidelity Benchmark for Fine-Grained Evaluation of CT Report Generation","venue":"cs.AI","work_id":"11d85088-ad4d-49a9-a938-b099cff14391","year":2026},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2604.24001","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:dd2bce26da4cc7cac09f49a84bb6c1e619bad6a32c6d0b712baf2e8310f61535","observation_id":"bf4a4430-b9b0-49e2-8636-0f67762f4306","resolution":{"observed_at":"2026-07-08T22:15:39.379540Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.953274Z","title":"Medical Image Computing and Computer Assisted Intervention (MICCAI) , year =","venue":null,"work_id":"bad66efa-a485-4c12-9345-0081b6eb610b","year":null},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:525c4c070bad5db5cd32988b225f8f2928cf4cd1839c27d3c1324e273da943ac","observation_id":"e1f52504-dfa6-402b-9406-d889adbb893c","resolution":{"observed_at":"2026-07-08T22:15:39.954872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07146","last_updated":"2025-02-25T06:17:52Z","snapshot_observed_at":"2026-08-08T00:50:15.023605Z","submitted_at":"2024-06-11T10:45:59Z","title":"Argus: Benchmarking and Enhancing Vision-Language Models for 3D Radiology Report Generation","version":3},"cited_work":{"arxiv_id":"2406.07146","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.07146","snapshot_observed_at":"2026-07-08T22:15:39.399939Z","title":"Argus: Benchmarking and Enhancing Vision-Language Models for 3D Radiology Report Generation","venue":"cs.CV","work_id":"8017dd3a-9bee-448e-9ae1-0205fd2267f8","year":2024},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"cited_paper":"/paper/2406.07146","citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:782301d680d6c6d99e6e08f4ce9b410741420eb237ccb719e25f6ba09f2f6e35","observation_id":"f269fb95-0bfe-40e0-a8cb-10fa0c87455c","resolution":{"observed_at":"2026-07-08T22:15:39.401300Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T22:15:39.915515Z","title":", title =","venue":null,"work_id":"21bcb689-e1dc-4ce5-b5e7-047eb32df1ee","year":2021},"citing_paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-07-08T22:06:55.065652Z"},"links":{"citing_paper":"/paper/2607.05880"},"observation_digest":"sha256:ab55e0e61bd8cc1195e37892261a338aa0b6c8464f6606557b2aa71aa3a90d57","observation_id":"2bd60ea7-f059-434e-a5cf-2745308e780a","resolution":{"observed_at":"2026-07-08T22:15:39.916787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2607.05880","last_updated":"2026-07-07T06:23:08Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-02T21:48:04.145448Z","submitted_at":"2026-07-07T06:23:08Z","title":"Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context"},"reference_resolution":{"displayed":73,"state_counts":{"malformed_identifier":0,"metadata_mismatch":15,"parse_uncertain":2,"unresolved":1,"verified_exact":8,"verified_fuzzy":47},"total_outbound_references":73},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 0 inbound Pith citation observations for arXiv:2607.05880."}