{"as_of":"2026-08-10T05:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:83497cd85672b78719f3116b98aa6d7e8db572ea00518a56fc5b833092397dc1","coverage":[{"denominator":16,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T18:22:08.048997Z","state":"measured"},{"denominator":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2502.00611/citation-record","integrity":"/paper/2502.00611/integrity","json":"/paper/2502.00611/citation-record.json","paper":"/paper/2502.00611"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.14325","last_updated":"2025-02-26T11:34:49Z","snapshot_observed_at":"2026-08-03T18:40:47.863426Z","submitted_at":"2024-06-20T13:56:42Z","title":"Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14325","snapshot_observed_at":"2026-08-09T18:22:07.975846Z","title":"and Kowald, D., 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:07.975846Z"},"links":{"cited_paper":"/paper/2406.14325","citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:15c289851c3623f539bc52e0b8461d79dfb338d01908527673c65e46061685c7","observation_id":"eb82b189-6de7-4583-a707-d7e85d6d07a4","resolution":{"observed_at":"2026-08-09T18:22:07.975846Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:22:08.413744Z","title":"Artificial intelligence faces reproducibility crisis","venue":null,"work_id":"0374985e-e3b8-4cb8-9e7a-c4f3d8c7e4dd","year":2018},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:07.981866Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:1b8c4340e09716c9f796ec4f55856da16fe6c8680ae7d41b526461c5c42b615b","observation_id":"cb240624-9091-4c54-b42b-d8f05f6ca517","resolution":{"observed_at":"2026-08-09T18:22:08.418708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.398664Z","title":"and Larochelle, H., 2021","venue":null,"work_id":"cb1de14d-1648-4032-a98c-d94120d9d774","year":2021},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:07.986839Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:fa2eaa59a68099fffeae47de3331fdf5bcecce13b3e8d5675cb00173fc3836f7","observation_id":"de4c11ac-5dd6-413b-a8ba-eeeb47d19e5e","resolution":{"observed_at":"2026-08-09T18:22:08.403386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.383905Z","title":"and Kjensmo, S., 2018, April","venue":null,"work_id":"683571b7-8511-4b1f-be59-b143408c7a7d","year":2018},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:07.991721Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:8f0a5c387f140f9b830c3ac67e2904f0a3a0bd31d2cd5582909d19043e741e55","observation_id":"dec96cb2-a304-4826-bed2-19160b1e8a9c","resolution":{"observed_at":"2026-08-09T18:22:08.388701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.368621Z","title":"and Dane, S., 2018","venue":null,"work_id":"21208a1a-5a90-4513-b456-46699fc31845","year":2018},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:07.996744Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:9f52c5ef6de1738a04682d8a94745bb1fe209b1b8ca68ad1cd450008d4886bd9","observation_id":"f0323530-1266-46c5-a05b-6b4d00b65e14","resolution":{"observed_at":"2026-08-09T18:22:08.373494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.352972Z","title":"The Foundations of Verification: Code Verifi- cation","venue":null,"work_id":"08fc9fab-f4e4-4b6a-8d0a-4098db23f095","year":2017},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.002044Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:b50f26e73b8af8fc3222ab15efaf9ac72643d4cf71fbb5f129e366aa6677ff62","observation_id":"3fb3b970-90f3-415c-a767-16a1e30876af","resolution":{"observed_at":"2026-08-09T18:22:08.357993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.337934Z","title":"A step toward quantifying independently reproducible machine learning research","venue":null,"work_id":"d4e5052d-46bd-4a0e-bd26-0b3895e392c4","year":2019},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.007381Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:8ce38695f777369ee933abd32a95e5a6ba5bb13193095d5f65d877a0a18523c0","observation_id":"2fffde67-a8ff-4d48-bc57-af39879153c1","resolution":{"observed_at":"2026-08-09T18:22:08.342719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.321886Z","title":"and Zuo, C., 2023","venue":null,"work_id":"e5cfb13b-7d6a-45cd-8eef-dc6a653952ed","year":2023},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.012063Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:1feaceb539df12d884a67ab185d6836f451f1f880a6b63d946b5ac4a5b0ff66b","observation_id":"c03b974b-87e4-4bac-9d2e-6607a2d03a17","resolution":{"observed_at":"2026-08-09T18:22:08.327044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.306837Z","title":"and Riedel, S.,","venue":null,"work_id":"955482d4-10ae-4be4-b388-ce1c7550af21","year":null},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.016754Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:e000c40c90a2f20395ae008947b7c82004e7ee01fab5de86b882b24103ebc3af","observation_id":"48a5c593-bafc-4f0e-afcc-ce2bfdc6402b","resolution":{"observed_at":"2026-08-09T18:22:08.311678Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.274118Z","title":"LlamaIndex","venue":null,"work_id":"a2168d54-924b-469a-bbeb-9452415b0601","year":2022},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.026127Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:77760221c73191129cce53d75ffb6c922597f4bfb375da902fd766c0cb0a56ad","observation_id":"668cc879-4ab0-4efe-b112-25f94823db81","resolution":{"observed_at":"2026-08-09T18:22:08.279058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.258888Z","title":"NVIDIA NeMo","venue":null,"work_id":"10c9ecbb-e974-483a-b25d-5a89aec8d352","year":2019},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.030747Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:aee44fb9398f9759ecded358d5d575809622f9a9b7de4fbe128b0197419ca854","observation_id":"ee38fee6-5824-4268-a165-c63c70dcbf07","resolution":{"observed_at":"2026-08-09T18:22:08.263625Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.143950Z","title":"Introducing Meta Llama 3: The most capable openly avail- able LLM to date","venue":null,"work_id":"179a4c1d-7ce3-4fdc-ad17-8ae5a5e2f0e4","year":2024},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.035355Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:bc6eb19d73d70ea057ae265b0c83bd2ec4daa6956f6f51b85766c854e9e9bd8b","observation_id":"aa45e365-ce3b-437e-84f1-5d35d6664d6d","resolution":{"observed_at":"2026-08-09T18:22:08.148312Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.17428","last_updated":"2025-02-25T00:35:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-05-27T17:59:45Z","title":"NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.17428","snapshot_observed_at":"2026-08-09T18:22:08.039790Z","title":"and Ping, W., 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.039790Z"},"links":{"cited_paper":"/paper/2405.17428","citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:5495174f6911b5546371d7b793b6f49a4b182f15474dba9fd9642b509f48da4c","observation_id":"b74179bb-0c8c-42fc-9f86-9a86e4ce5f31","resolution":{"observed_at":"2026-08-09T18:22:08.039790Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T18:22:08.128478Z","title":"NVIDIA Retrieval QA Mistral 4B Reranking v3","venue":null,"work_id":"518224a4-ec86-4486-a9f5-9b1ab55474dc","year":2024},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.044594Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:80b4c348c39c5174afb90cd1851feb09ca3e9fd9908e23b37e57136a1cee763f","observation_id":"f301ee5b-2ea3-482a-a847-acac5b734c33","resolution":{"observed_at":"2026-08-09T18:22:08.134001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.111160Z","title":"and Toutanova, K., 2019, June","venue":null,"work_id":"46823d1a-37da-4a52-a05a-a05d5e50411e","year":2019},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.048997Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:3bc635b0df10950b10cbc1a78c600510f4904e1e7a9dd4ffc8cfacc619d718d7","observation_id":"ac984c04-f3cc-4fb4-a13b-8b9c190462ca","resolution":{"observed_at":"2026-08-09T18:22:08.117292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T18:22:08.290814Z","title":"Advances in Neural Information Processing Systems","venue":null,"work_id":"c59e5b8b-4ec1-42c2-bdb7-cc8e1d169271","year":null},"citing_paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-09T18:22:08.021575Z"},"links":{"citing_paper":"/paper/2502.00611"},"observation_digest":"sha256:34580567027abeedb8e969d4e55204647e580806c9bf5fa951f12c6f90316ece","observation_id":"59474ca0-ea30-40b5-bd84-51b9df20c135","resolution":{"observed_at":"2026-08-09T18:22:08.295790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.00611","last_updated":"2025-02-02T00:35:42Z","latest_version":1,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-09T23:11:30.432913Z","submitted_at":"2025-02-02T00:35:42Z","title":"Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation"},"reference_resolution":{"displayed":16,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":2,"verified_exact":0,"verified_fuzzy":14},"total_outbound_references":16},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2502.00611."}