{"as_of":"2026-08-20T01:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0432014fad0fa840104dd1cc7e42446cf7a7ed37ed8eea135b3de27d47a08e67","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:26:50.347920Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+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/1908.07209/citation-record","integrity":"/paper/1908.07209/integrity","json":"/paper/1908.07209/citation-record.json","paper":"/paper/1908.07209"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:26:51.126872Z","title":"Computational Exploration of Molecular Scaffolds in Medicinal Chemistry","venue":null,"work_id":"af1640f8-e5eb-45c5-af33-96faf3ead211","year":2016},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.154125Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:6b8f292a81127c56e8188cf0cd65e3cdc7e527397e5867d90c0c027fb47e0410","observation_id":"99d51617-d2c3-4b4f-bf73-dd71acf14976","resolution":{"observed_at":"2026-08-14T12:26:51.131990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:51.112240Z","title":"W.; Murcko, M","venue":null,"work_id":"f8afc265-948d-46ff-9e51-53a7fc8df6b1","year":1996},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.159516Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:82a6b437e02c8968c2b280f7c31e7b7d5eafa0fdf41dbe90e2558981bc7a8075","observation_id":"38a13a73-ea8f-4e9b-b805-3bea9d8a33ad","resolution":{"observed_at":"2026-08-14T12:26:51.116850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:51.097407Z","title":null,"venue":null,"work_id":"3ea85b25-344f-4703-a6d2-f4120208ceeb","year":2015},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.164657Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:cbb47be763f4e1286e95e86ca12ee325b471490fcbb5bd680faf34360bd9b288","observation_id":"4a57eb3e-1192-451d-90bf-6d13111b3898","resolution":{"observed_at":"2026-08-14T12:26:51.102044Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:51.082763Z","title":"Mining for bioactive scaffolds with scaffold networks: improved compound set enrichment from primary screening data","venue":null,"work_id":"6078f942-80ff-43ba-aa8a-4d3765975421","year":2011},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.169377Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:a8a2ecc4d425a407d4bcbd0789e4e1b14e685aed6d74cd040f3f364d5ba56440","observation_id":"c36410a9-597a-4d67-8799-a4f0b069d301","resolution":{"observed_at":"2026-08-14T12:26:51.087673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:51.067443Z","title":"Identification of Bioactive Scaffolds Based on QSAR Models","venue":null,"work_id":"1fa3380d-dc5c-452b-ac8e-31d4b0964c86","year":2018},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.174884Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:3af862a4da144e46bcb02321ef842ed58016ed5f153614229dc94290f54bc174","observation_id":"552dce15-bbce-4a4f-9f12-a50efd9e2a7e","resolution":{"observed_at":"2026-08-14T12:26:51.072682Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:51.051117Z","title":"N.; Zhang, J.-H.; Raman, P.; Ertl, P.; Schuffenhauer, A","venue":null,"work_id":"a4101078-f755-4937-b4a6-05a2b6abeaf1","year":2010},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.179889Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:2aa32b2095ccfe475fa5682fefd8d9fb992603300f0741ab6418db680114bccd","observation_id":"36c72cb6-f7cf-49b1-9b36-3c5369719fd8","resolution":{"observed_at":"2026-08-14T12:26:51.056020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:51.036545Z","title":"J.; Janes, J.; Su, A","venue":null,"work_id":"1bf566e0-408a-410a-ab9d-9e312d8bd510","year":2005},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.185821Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:050e21670deda78bda8d920fbd950cb3ccf2248c48eaa4eb8ad07fd01f7cf9db","observation_id":"3fe11681-7010-4765-8a92-c6b5f483d9eb","resolution":{"observed_at":"2026-08-14T12:26:51.041134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:51.021572Z","title":"A.; Schuffenhauer, A.; Scheck, M.; Wetzel, S.; Casaulta, M.; Odermatt, A.; Ertl, P.; Waldmann, H","venue":null,"work_id":"9eccb851-f31a-43b0-ba2f-2acfea526755","year":2005},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.190920Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:41b6353b91c324a2f0db54b46f0e4fe9c97254b175b1c3413ca4552f3fb77b3d","observation_id":"f5fe52e6-330c-4b53-9033-2928a352bc6a","resolution":{"observed_at":"2026-08-14T12:26:51.026561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:51.007210Z","title":"A.; Waldmann, H","venue":null,"work_id":"05eb3ea2-0d0e-4ff4-8741-bab52f4677eb","year":2007},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.195898Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:0519ba462b04a570c79055435ff5b258af881a8f641b641a45e4c078c4414d3c","observation_id":"acde0b19-78c1-44c8-b909-4b9fa3f43069","resolution":{"observed_at":"2026-08-14T12:26:51.011726Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.992635Z","title":"Scaffold Hunter: a comprehensive visual analytics framework for drug discovery","venue":null,"work_id":"75c27774-7636-4ff5-b284-ac8a18798609","year":2017},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.200648Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:29c2e6067a790dea4220129640fa0a3a8bacb89148a608db6100ca4d5dd8f546","observation_id":"4bfa81e5-7b9b-4672-91c6-7783d9fa7c80","resolution":{"observed_at":"2026-08-14T12:26:50.997139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.977072Z","title":"Deep learning","venue":null,"work_id":"defb72c7-d874-45bf-9609-00dc3d0ea9bc","year":2015},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.205142Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:5c3458d380074d47d10dad46cc37467506cb2f705f01aaa6a188c378d43aab59","observation_id":"49945360-e38c-4218-a72e-202304281e5d","resolution":{"observed_at":"2026-08-14T12:26:50.981550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.962859Z","title":null,"venue":null,"work_id":"949ef57b-2179-47c4-aeef-d7b8ff608596","year":null},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.209747Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:2bd10d3ed9efab006a1856f7b777d763511e50dd01e37d7892217a9f549b6c67","observation_id":"a4aa361b-e34f-4045-8c95-819c917e8c99","resolution":{"observed_at":"2026-08-14T12:26:50.967584Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.948709Z","title":"Computer-based de novo design of drug-like molecules","venue":null,"work_id":"13f941e0-a698-4af5-9f13-462ec0222c5c","year":2005},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.214383Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:fa363e8408bce49ce2aad92a5aa913d344c9294b856738c232294ffc62723376","observation_id":"9c37dddf-b0c2-40f6-af64-af88a9a88dac","resolution":{"observed_at":"2026-08-14T12:26:50.953544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.935019Z","title":null,"venue":null,"work_id":"f70bea53-bce2-48a5-b9d6-7f4057ab683a","year":2018},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.218788Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:0877ecd0b8fe95222d32f60b6bbaa114457b9b65a67d2d2a136d1a0a148b1792","observation_id":"1dcbb9e0-418b-4694-8ca3-7f2659af701d","resolution":{"observed_at":"2026-08-14T12:26:50.939439Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.920683Z","title":"N.; Duvenaud, D.; Hernandez-Lobato, J","venue":null,"work_id":"5890867a-0eed-43c9-8149-1703a767f2fb","year":2018},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.223423Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:b0b1f7df5cd84c96314b339a448e2a01eea549b50c1aca07c7a28c1acdee8945","observation_id":"46fbc3ef-a0f9-4f7b-9173-4a95fcb6748f","resolution":{"observed_at":"2026-08-14T12:26:50.925498Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.906036Z","title":"Molecular de-novo design through deep reinforcement learning","venue":null,"work_id":"c5450510-66a6-400f-afb2-d7fd5b5ebe5c","year":2017},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.227934Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:f332b23932468c04c10cf361bd0c4f84de9926da486f76f8bccffc200aea1c2e","observation_id":"7af2808c-d281-4b43-8a3c-6f2e669a552e","resolution":{"observed_at":"2026-08-14T12:26:50.910897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.891443Z","title":"SMILES, a chemical language and information system","venue":null,"work_id":"d8201ad3-79a9-4ddc-bdd5-3a9e294de622","year":1988},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.232645Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:3d158eae36c0c351f44b2955616be021171ff44b52e11e8d4cfd387cbc52a271","observation_id":"378395f4-854f-4195-868b-263647d65553","resolution":{"observed_at":"2026-08-14T12:26:50.896448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.876347Z","title":"Multi-objective de novo drug design with conditional graph generative model","venue":null,"work_id":"9f172302-fd7d-4bdf-bf6f-e92a2275e1ef","year":2018},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.237170Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:5a85377c7fec6bff720134970c2ab7646a60a1dfa7ff6cfa4db8a4f3533554eb","observation_id":"6eda960a-c95c-4fe3-a1f5-70dfbc2a9e28","resolution":{"observed_at":"2026-08-14T12:26:50.881317Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1610.02920","last_updated":"2016-11-09T15:22:28Z","snapshot_observed_at":"2026-08-18T11:32:25.128938Z","submitted_at":"2016-10-10T14:02:30Z","title":"Generative Adversarial Nets from a Density Ratio Estimation Perspective","version":2},"cited_work":{"arxiv_id":"1610.02920","doi":null,"metadata_source":"pith","pith_arxiv_id":"1610.02920","snapshot_observed_at":"2026-08-14T12:26:50.611987Z","title":"Generative Adversarial Nets from a Density Ratio Estimation Perspective","venue":"stat.ML","work_id":"ea5647bc-461f-452c-bf78-1fbc26099924","year":2016},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.241960Z"},"links":{"cited_paper":"/paper/1610.02920","citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:e59af6f25c580713821c6f1987f3e0a95d132c8d7b1ca21edb9f4fa464b83c4c","observation_id":"20c0a26a-8699-49a7-8637-6181e3f14c83","resolution":{"observed_at":"2026-08-14T12:26:50.618326Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.03324","last_updated":"2018-03-08T22:20:00Z","snapshot_observed_at":"2026-08-14T19:37:59.979230Z","submitted_at":"2018-03-08T22:20:00Z","title":"Learning Deep Generative Models of Graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.03324","snapshot_observed_at":"2026-08-14T12:26:50.247346Z","title":"Learning Deep Generative Models of Graphs","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.247346Z"},"links":{"cited_paper":"/paper/1803.03324","citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:113ff5b0d2597ca6d206404aaf77ad4444bc1cd7ce2d782c2b691de3b289079d","observation_id":"b9648bb4-3c4c-4a24-b76f-a2e6f5d62ff2","resolution":{"observed_at":"2026-08-14T12:26:50.247346Z","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":"2026-08-14T12:26:50.862024Z","title":"L.; Leskovec, J","venue":null,"work_id":"fdc27ab9-b3f1-40b8-9ed1-dde867c1f1bf","year":null},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.252632Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:b7ae67c48d2fd8ea7f4b533cf8f8225063395344275ae1f4e7926db63a396ae7","observation_id":"7ba1cd20-826e-4f49-9daf-4c065c182e57","resolution":{"observed_at":"2026-08-14T12:26:50.866628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.847609Z","title":"Junction Tree Variational Autoencoder for Molecular Graph Generation","venue":null,"work_id":"8437c32c-f94e-41be-869f-8cfdd1d676f1","year":null},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.257180Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:5e8719c4e1ed981279c28212f7a0c064dceadba83225ed14f2edc7b9dfdcf511","observation_id":"d2c89e71-1dc6-43b3-808b-60d29f69ed59","resolution":{"observed_at":"2026-08-14T12:26:50.852326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.11973","last_updated":"2022-09-27T10:04:29Z","snapshot_observed_at":"2026-08-18T21:41:18.108090Z","submitted_at":"2018-05-30T13:56:06Z","title":"MolGAN: An implicit generative model for small molecular graphs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.11973","snapshot_observed_at":"2026-08-14T12:26:50.262302Z","title":"MolGAN: An implicit generative model for small molecular graphs","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.262302Z"},"links":{"cited_paper":"/paper/1805.11973","citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:4f77722c85d1975b06a739a7929da34943e6f50467cdc050264c41f3b8db883f","observation_id":"144c35f1-e0b3-4faf-a307-6592f14212c9","resolution":{"observed_at":"2026-08-14T12:26:50.262302Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.02032","last_updated":"2018-09-05T17:19:41Z","snapshot_observed_at":"2026-08-18T03:04:53.728674Z","submitted_at":"2018-09-05T17:19:41Z","title":"Latent Molecular Optimization for Targeted Therapeutic Design","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.02032","snapshot_observed_at":"2026-08-14T12:26:50.267425Z","title":"Latent Molecular Optimization for Targeted Therapeutic Design","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.267425Z"},"links":{"cited_paper":"/paper/1809.02032","citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:9145ca3507793c9a375fd07b4d7ff9dd4779e657ff89885f32dcd0f321b639d0","observation_id":"3206e465-7863-41e1-8b77-6d55c6eeb59c","resolution":{"observed_at":"2026-08-14T12:26:50.267425Z","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":"2026-08-14T12:26:50.832701Z","title":"QBMG: quasi-biogenic molecule generator with deep recurrent neural network","venue":null,"work_id":"5b95961e-0cf5-4fb5-8140-25c08fe8d73c","year":2019},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.272234Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:57ed1c29c6c222f99107869d9fa75ca49a2f12b0f7d3f222354c941319ffd217","observation_id":"e2ceb958-66b6-46da-beb7-ff43ad4a8943","resolution":{"observed_at":"2026-08-14T12:26:50.837681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.13639","last_updated":"2019-05-31T14:34:35Z","snapshot_observed_at":"2026-08-18T03:05:20.126173Z","submitted_at":"2019-05-31T14:34:35Z","title":"Scaffold-based molecular design using graph generative model","version":1},"cited_work":{"arxiv_id":"1905.13639","doi":null,"metadata_source":"pith","pith_arxiv_id":"1905.13639","snapshot_observed_at":"2026-08-14T12:26:50.540472Z","title":"Scaffold-based molecular design using graph generative model","venue":"cs.LG","work_id":"7c1723c7-109a-4b65-9dd2-3967a9b6ce69","year":2019},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.276625Z"},"links":{"cited_paper":"/paper/1905.13639","citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:32fc84f06076d26385a9d0d5e2a72b1e612093bdc99004d2007fbfa5b5f251ed","observation_id":"edd6e24b-ee04-437b-aad4-2f9611df11b9","resolution":{"observed_at":"2026-08-14T12:26:50.546126Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.818195Z","title":"J.; Bento, A","venue":null,"work_id":"4e8a7bf0-3b87-45a9-b11d-352907bf7e0b","year":2012},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.281672Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:6d0bf5c19052e68bd45d0eca75d43d7d20c262590187bcbab2e94ed7e79f2e07","observation_id":"38b87644-be85-4e37-b39a-a2255cba1498","resolution":{"observed_at":"2026-08-14T12:26:50.822796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.800903Z","title":"R.; Paolini, G","venue":null,"work_id":"a8adda7d-4195-4bfe-9f29-8132cac02568","year":2012},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.286417Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:2fc5e239ced48832ca5a8b311fa16c30ac9107c5f3dcea50352d535f38df3b22","observation_id":"36a6a34b-3ff1-4ed7-b872-e39280f9db7e","resolution":{"observed_at":"2026-08-14T12:26:50.808450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.785012Z","title":"Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions","venue":null,"work_id":"2cfee829-4e1f-465c-a2fa-cb2bc8fa1fdd","year":2009},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.290909Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:225a22f726d47e5defc97ed857f8f6b15052ae25b1c8ee6ae06a6fa708e42816","observation_id":"fa89c916-54c7-4ede-bbb3-96dec2bfe7ed","resolution":{"observed_at":"2026-08-14T12:26:50.790664Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.769937Z","title":"P.; Welling, M","venue":null,"work_id":"b3cf6f39-57d0-4980-8de0-a7314d5e492b","year":null},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.295194Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:29615ff9f24a7b28337d1a32858780477f301829720401f326a37b5aba510fa6","observation_id":"474e0190-eb09-4a85-8fd1-55c3a9d8acd6","resolution":{"observed_at":"2026-08-14T12:26:50.774968Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.755915Z","title":"R.; Vilnis, L.; Vinyals, O.; Dai, A","venue":null,"work_id":"9bd00403-6164-4bec-83a0-d97874d8dd67","year":null},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.299731Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:9aa7db93ccf2555beb700cfa62c5bb6913bc669fc2304f6da31480751b2e3c87","observation_id":"270db600-2c49-4f0f-b599-36378a66c901","resolution":{"observed_at":"2026-08-14T12:26:50.760450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.740654Z","title":"beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework","venue":null,"work_id":"21e137ec-1ef7-4322-8218-698556e0bc9c","year":2017},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.304977Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:3fb12eca26c3ab19300b0eae3772878e433d470b3d9990d70e59e8a9f45254fa","observation_id":"650e289a-e4ff-4d92-865c-e486bf156bb0","resolution":{"observed_at":"2026-08-14T12:26:50.745375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.08227","last_updated":"2017-08-31T14:14:29Z","snapshot_observed_at":"2026-08-18T03:00:52.494790Z","submitted_at":"2017-08-28T08:02:55Z","title":"ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity?","version":3},"cited_work":{"arxiv_id":"1708.08227","doi":null,"metadata_source":"pith","pith_arxiv_id":"1708.08227","snapshot_observed_at":"2026-08-14T12:26:50.517008Z","title":"ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity?","venue":"stat.ML","work_id":"5a586b93-e299-4063-86ad-45c68903fc59","year":2017},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.309301Z"},"links":{"cited_paper":"/paper/1708.08227","citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:0d13b523de431b49345f7bb0af7e93c7aeaa9605db7882b950ec4b489240f2dd","observation_id":"d4c46460-27a7-4400-9762-c9a76fb18d68","resolution":{"observed_at":"2026-08-14T12:26:50.524190Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.726263Z","title":"Mmd gan: Towards deeper understanding of moment matching network","venue":null,"work_id":"1e8edfbf-6a62-490d-b7a8-f24febf7b72d","year":null},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.314635Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:842b955a023af2e28543cf67e3e666e2f34a4a85eab0bc4661ff872856cf51f9","observation_id":"bd87c022-7140-4ee5-8127-e8fb827d516f","resolution":{"observed_at":"2026-08-14T12:26:50.730824Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.711417Z","title":"H.; Taylor, G","venue":null,"work_id":"fe331773-2707-4968-977b-ec8b1d5fd40e","year":null},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.319778Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:50833d79d4dfab7175962af005e19d58f897f6a4bc28c8b9b706be77fd398e8b","observation_id":"28e78e2f-3882-4145-839f-1e0183a6d855","resolution":{"observed_at":"2026-08-14T12:26:50.716243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.695487Z","title":"Wasserstein GAN","venue":null,"work_id":"4b8f7bfa-8322-4c26-aa29-051d2b37d19a","year":null},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.325389Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:3b2f8bf52542cabd37cc6d67bad96c35922c8b52fd18e4eb40cfcd6319ed50b8","observation_id":"376ff329-e8e1-41da-af89-87526122698a","resolution":{"observed_at":"2026-08-14T12:26:50.700049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.680061Z","title":"Frechet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery","venue":null,"work_id":"b43a23d9-34cf-424b-a077-f3b3f64c6c38","year":2018},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.329932Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:e5de1d06a5861b2aed9c58ddea4793a879dbaa92c6313aec12eb40c9ecae7e74","observation_id":"70e25938-7718-40a3-95c7-736a9dcde382","resolution":{"observed_at":"2026-08-14T12:26:50.685153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.663319Z","title":null,"venue":null,"work_id":"ba099b96-368c-4168-b88d-904043c4fae4","year":1971},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.334278Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:df08052c271552966bbb000c014a82498c6f27f1add3ccd85a917be23b7c2b64","observation_id":"beb75164-cb08-44cb-8ce2-dec4244a98cd","resolution":{"observed_at":"2026-08-14T12:26:50.668531Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.646068Z","title":null,"venue":null,"work_id":"0d30c2de-4568-4912-8480-ef40ced70cef","year":2013},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.338763Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:02ce238ff463246b2e8b2e935f57f111d98f2e50dd58648e43f7377becd4c1f6","observation_id":"a264ab76-cad8-4c7d-8130-2512b535fc36","resolution":{"observed_at":"2026-08-14T12:26:50.651498Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.629810Z","title":"P.; Salimans, T.; Duan, Y.; Dhariwal, P.; Schulman, J.; Sutskever, I.; Abbeel, P","venue":null,"work_id":"468b683d-a578-468e-a8dd-6b2f7e807bcb","year":null},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.343511Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:bd277a5ec26d292f811e7b33f6a6aa2ed944af403a7b171434f1fc336b988cd9","observation_id":"3e6122a6-7380-44e6-9b99-9c64f95fa711","resolution":{"observed_at":"2026-08-14T12:26:50.634785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-14T12:26:50.347920Z","title":"6DTpDQ 2(C","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning","version":4},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-14T12:26:50.347920Z"},"links":{"citing_paper":"/paper/1908.07209"},"observation_digest":"sha256:7574aaa29250959c3bb69156a8825d90a082dd3dfdfe60bd548721e50a5a3322","observation_id":"08ec85fd-18bd-41d6-9531-45df1d28a9e0","resolution":{"observed_at":"2026-08-14T12:26:50.347920Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"1908.07209","last_updated":"2019-09-05T00:47:25Z","latest_version":4,"primary_category":"q-bio.QM","snapshot_observed_at":"2026-08-19T16:13:45.216930Z","submitted_at":"2019-08-20T08:04:00Z","title":"DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":1,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":8,"verified_exact":2,"verified_fuzzy":29},"total_outbound_references":41},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:1908.07209."}