{"as_of":"2026-08-16T19:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b6e0788fc39be5777c93511fe267b4b2a64e5d73014301c81e9ff2758dcce10c","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":"2026-08-14T12:52:14.032901Z","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":"2026-08-16T06:30:59.297886+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/1908.06416/citation-record","integrity":"/paper/1908.06416/integrity","json":"/paper/1908.06416/citation-record.json","paper":"/paper/1908.06416"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:52:14.212720Z","title":"Scaling learning algorithms towards AI","venue":null,"work_id":"c2d5a4ef-c7c7-4482-89d5-2a85fc8aa00b","year":2007},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:13.973743Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:b39b87cccd0aa9d72b020a65fb194e65ba2996cadb24d4deab02eb681fe909a8","observation_id":"5751081e-b739-40ba-a847-1da6d8416cd8","resolution":{"observed_at":"2026-08-14T12:52:14.216482Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:52:13.978149Z","title":"Representation learning: A review and new perspectives","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:13.978149Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:5648536b459ea9371ed5f9b84d65dde36e7822377c1480e247108a3a646193a6","observation_id":"e7904613-385e-434f-845a-cf3e9914fca8","resolution":{"observed_at":"2026-08-14T12:52:13.978149Z","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":"2026-08-14T12:52:14.202296Z","title":"Approximating CNNs with bag-of-local- features models works surprisingly well on ImageNet","venue":null,"work_id":"9f643238-6ce2-4f1f-9f5c-4d707e20501d","year":2019},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:13.981960Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:1835c98a2f879fc22712f366badc847d37a07e6d7aa62fb74b004c00ed50d4a8","observation_id":"9f81fda1-0045-4a58-a304-093e0293d3fb","resolution":{"observed_at":"2026-08-14T12:52:14.205931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:52:13.985690Z","title":"He et al","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:13.985690Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:3700439b45c0eaae6481f8f4380b673d1289c97b0ff2d23a46a19c8a865409be","observation_id":"f6e866f7-cc3d-4716-b0eb-bd6f03225bcf","resolution":{"observed_at":"2026-08-14T12:52:13.985690Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.11561","last_updated":"2017-11-30T18:30:49Z","snapshot_observed_at":"2026-08-14T20:08:18.035712Z","submitted_at":"2017-11-30T18:30:49Z","title":"Measuring the tendency of CNNs to Learn Surface Statistical Regularities","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.11561","snapshot_observed_at":"2026-08-14T12:52:13.989552Z","title":"Measuring the tendency of CNNs to learn surface statis- tical regularities","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:13.989552Z"},"links":{"cited_paper":"/paper/1711.11561","citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:f264f37ad8c290f861454fd7861c14ba1323928561f7243c9a7c14f8555b177a","observation_id":"b3da2436-6547-49a5-8c9b-35b65b08c6c5","resolution":{"observed_at":"2026-08-14T12:52:13.989552Z","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":"2026-08-14T12:52:14.190378Z","title":"Generalization in deep learning","venue":null,"work_id":"618e1d3c-bcfb-48c4-8dbc-82c24f121746","year":2018},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:13.993892Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:5c40b9eda9436cb959af5ff4a4e4c6cffe904b45eb029866f79a3ffea9c28d17","observation_id":"31af8b7e-16b3-4150-a11a-337916496a20","resolution":{"observed_at":"2026-08-14T12:52:14.194303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:52:14.178793Z","title":"Learning multiple layers of features from tiny images","venue":null,"work_id":"50760acf-f107-48d8-bb71-818793118bc0","year":2009},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:13.997985Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:01adc8abd75a93da5ea1c6a65a0cb7ba437f13cfe57a821d013ab389d992ec2d","observation_id":"1dd58e85-56a8-490f-bcaf-a485dfd6c02d","resolution":{"observed_at":"2026-08-14T12:52:14.182636Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:52:14.166914Z","title":null,"venue":null,"work_id":"3fe1284f-a07c-4dc8-9b8e-1d6c65ccbd63","year":null},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:14.001544Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:f1c2e94cb04cf79bd4bbb1ce00c2bf4abc8493fbe73f19ce12afc5623e26c6b8","observation_id":"dbb62da3-e07c-4d35-bb85-f2189a079f67","resolution":{"observed_at":"2026-08-14T12:52:14.171327Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:52:14.156151Z","title":"Understanding the effective receptive field in deep convolutional neural networks","venue":null,"work_id":"e28d697c-f549-4a18-aa9d-1e81257e183e","year":2016},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:14.006553Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:43d6d4520a250af0588f3fd64d2b2cad66d5286dbcfd9c68cd7a42ee3cb2700e","observation_id":"60da2687-c3fa-4f18-b182-9e3efc6b805f","resolution":{"observed_at":"2026-08-14T12:52:14.159853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:52:14.145516Z","title":null,"venue":null,"work_id":"7d28c2ad-1f6a-4333-8de8-fc96813f6d66","year":2016},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:14.010023Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:ed8aef94bde399fa7aab0aa5e73fa38cbc53788c1248cb170337f5b576dd08b3","observation_id":"93972012-aac1-4a9e-aedb-816b9357b0e5","resolution":{"observed_at":"2026-08-14T12:52:14.149060Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:52:14.013432Z","title":"Simonyan and A","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:14.013432Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:fb2065415e130fca7699020c32f3437e04cef5a2b2f3365818326089dc49cf12","observation_id":"75fa7258-1e71-4b50-9a2a-81dae5f85f98","resolution":{"observed_at":"2026-08-14T12:52:14.013432Z","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":"2026-08-14T12:52:14.128257Z","title":"On the depth of deep neural networks: A theoretical view","venue":null,"work_id":"dbbeba71-009c-44b5-9d39-2f8cc4d23ea0","year":2016},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:14.016876Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:a94a5ea2db59b5361a10ad05e7b8770ac778dee6728bc3ee22f726bbf4f3d638","observation_id":"563441d7-fe41-4f88-83da-fcc136c4a72c","resolution":{"observed_at":"2026-08-14T12:52:14.132235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:52:14.115791Z","title":"Regularization of neural networks using dropconnect","venue":null,"work_id":"75ef1a69-27c5-474c-846d-6144e932addf","year":2013},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:14.020555Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:452e4715284e146038b19848e86cc16994735ad6e10d066954231ad7f6113457","observation_id":"61e8398b-7a98-41bc-b0cc-f76b75d0b4a9","resolution":{"observed_at":"2026-08-14T12:52:14.120734Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.07747","last_updated":"2017-09-15T21:29:49Z","snapshot_observed_at":"2026-08-13T15:13:33.081929Z","submitted_at":"2017-08-25T14:01:29Z","title":"Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.07747","snapshot_observed_at":"2026-08-14T12:52:14.024884Z","title":"Fashion-MNIST: a novel image dataset for benchmarking machine learning algorithms","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:14.024884Z"},"links":{"cited_paper":"/paper/1708.07747","citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:e763f2793f492edd6531ffa4afef9847dd455161d51dd6d25dfc36db8ca9cde2","observation_id":"f02fea14-e922-420c-9477-40c8fd592c07","resolution":{"observed_at":"2026-08-14T12:52:14.024884Z","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":"2026-08-14T12:52:14.104171Z","title":"Zeiler and Rob Fergus","venue":null,"work_id":"2fa54f06-4624-47f6-8769-6d62be352be0","year":2014},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:14.028571Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:9430bd35fd2e5cb5daa7afbb599e29be1a9042621ffe0dbd8beb41e69dc49378","observation_id":"e4607cf5-5a60-43ec-8cf7-9b0b077db65c","resolution":{"observed_at":"2026-08-14T12:52:14.108411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:52:14.091471Z","title":"effective","venue":null,"work_id":"e789b1c4-dc35-4948-be65-d89a59c6cfd9","year":2018},"citing_paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T12:52:14.032901Z"},"links":{"citing_paper":"/paper/1908.06416"},"observation_digest":"sha256:408b0b3d19cfb23d4f1b600a9bda5ccf4dfe379dcc275b27711b36e62085764c","observation_id":"aac0a3fa-f748-4067-9ac2-57a025f921f5","resolution":{"observed_at":"2026-08-14T12:52:14.096208Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.06416","last_updated":"2019-11-29T16:35:10Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T02:25:04.237096Z","submitted_at":"2019-08-18T10:05:24Z","title":"Investigating Convolutional Neural Networks using Spatial Orderness"},"reference_resolution":{"displayed":16,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":9},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:1908.06416."}