{"as_of":"2026-08-16T09:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6644c20d683bf61b01667758fda00e6170a10e2e1177e9ef49a2139b69b16d35","coverage":[{"denominator":14,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:42:51.403085Z","state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"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/1908.06874/citation-record","integrity":"/paper/1908.06874/integrity","json":"/paper/1908.06874/citation-record.json","paper":"/paper/1908.06874"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:42:51.627449Z","title":"Effective rule-based multi-label classiﬁcation with learning classiﬁer systems","venue":null,"work_id":"327b67cb-3b61-476e-bf31-82ce0c4d046f","year":2013},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.343115Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:8c2a13a667d4ab4503e35d114f1d4ef4a98fae2bd24f21b40317eee5db0ec075","observation_id":"930de1e7-501a-4aa8-8336-b7131aebb0a8","resolution":{"observed_at":"2026-08-14T12:42:51.632141Z","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":"2026-08-14T12:42:51.612031Z","title":"An evolutionary multi label classiﬁcation using associative rule mining for spatial preferences","venue":null,"work_id":"a71cc29f-ee5c-4fe9-9a28-47e4aa64ef20","year":2011},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.348441Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:30baebde4477b41f9d6f57cf6dd7e77a3a36b061cee39293a4ed6de873a6ed4d","observation_id":"54890fc7-f21f-48ae-a686-187297c8ef6d","resolution":{"observed_at":"2026-08-14T12:42:51.617209Z","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":"2026-08-14T12:42:51.597960Z","title":"Evolving multi-label clas- siﬁcation rules with gene expression programming: A preliminary study","venue":null,"work_id":"7624e2a1-dbc8-4a13-b529-19d87bfd3e96","year":2010},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.353191Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:cc634f6785be7004dd60206e52cdd329bee9a6d0c4c1ad2a70a3ce57355f7e51","observation_id":"d29db1a2-b9f4-44a8-a352-60a52334b6bd","resolution":{"observed_at":"2026-08-14T12:42:51.602629Z","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":"2026-08-14T12:42:51.583729Z","title":"LI-MLC: A label inference methodology for addressing high dimensionality in the label space for multilabel classiﬁcation","venue":null,"work_id":"de70b981-86ca-4b30-ba5b-6267ab827562","year":2014},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.358081Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:475aa8a0dc8a31c0bbc89a14b9c7e4e9f990a2bb51445387b9a3758e040762e1","observation_id":"22506194-a706-421d-b0a4-45dd1276ab30","resolution":{"observed_at":"2026-08-14T12:42:51.588545Z","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":"2026-08-14T12:42:51.569311Z","title":"On label dependence and loss minimization in multi-label classiﬁcation","venue":null,"work_id":"f62b337f-6047-4c8d-b654-311eca0f7891","year":2012},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.362787Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:efb1e57f6ef1ab31e4e1aa5b731bbd6fbd465cfa6a4f8d0da99b3e629c09bfe5","observation_id":"00ea003c-2451-4111-a828-2322a83c89ed","resolution":{"observed_at":"2026-08-14T12:42:51.573946Z","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":"2026-08-14T12:42:51.554877Z","title":"Interpretable decision sets: A joint framework for description and prediction","venue":null,"work_id":"7829c9e1-a898-4644-90eb-fce6bd790a64","year":2016},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.367472Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:43ffde6f74b39069cc15a7180c96869626a2cf8e0b84768f011d0b82b7178f71","observation_id":"bf4d03f9-6379-4a7d-bc64-912be2d4388a","resolution":{"observed_at":"2026-08-14T12:42:51.559705Z","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":"2026-08-14T12:42:51.540720Z","title":"Multi-label Classiﬁcation based on Association Rules with Application to Scene Classiﬁcation","venue":null,"work_id":"bac5d28a-0057-4768-93a8-9fb4231d4fdc","year":2008},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.372943Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:20a1434f989d130be2ee3fb04cdd63f44256ac3db16fd5e5dd26ccf507626991","observation_id":"044b55fc-1736-4f02-b23d-9e97c88e4ca8","resolution":{"observed_at":"2026-08-14T12:42:51.545354Z","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":"2026-08-14T12:42:51.526291Z","title":"Learning interpretable rules for multi-label classiﬁcation","venue":null,"work_id":"d926cb67-22ac-416b-b594-a381e124c6eb","year":2018},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.377434Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:af5a02665326d3c85039cf334ac7d6101a62ebd861346ca79f2ab9e6317cf44c","observation_id":"2c95a144-dfc8-4daa-8436-49a62d8f18e6","resolution":{"observed_at":"2026-08-14T12:42:51.530755Z","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":"2026-08-14T12:42:51.510843Z","title":"Learning rules for multi-label classiﬁcation: A stacking and a separate-and-conquer approach","venue":null,"work_id":"b06fa2f8-5ffe-415d-a4bc-320dfdb45bb7","year":2016},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.381547Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:78904c474e93d84a8875a5c7fd8ccf9f84191d055472190c5e65945c381967cf","observation_id":"f2dc6764-7d76-40a9-9be5-9b184a070d04","resolution":{"observed_at":"2026-08-14T12:42:51.516006Z","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":"2026-08-14T12:42:51.494777Z","title":"Discovering and exploiting deterministic label relationships in multi-label learning","venue":null,"work_id":"ac9857ad-379b-484b-bf7a-ac85437fdba7","year":2015},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.385906Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:bf3d8bdea94354005784a7f391f88f266318780cb5a2bf076b994f64883ac1e1","observation_id":"e9091d7e-f2b4-41ac-8238-bfa2aba2960c","resolution":{"observed_at":"2026-08-14T12:42:51.499806Z","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":"2026-08-14T12:42:51.479814Z","title":"Multi-label classiﬁcation with label constraints","venue":null,"work_id":"308d3360-b6e7-4c30-9ef2-c763bd857054","year":2008},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.390083Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:db31c01cf192659bcd4007aaaaffde261341c17c9169f3b572f4f6b4813b2945","observation_id":"14fade10-2c17-4121-8522-8ff833ff5a43","resolution":{"observed_at":"2026-08-14T12:42:51.484513Z","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":"2026-08-14T12:42:51.465073Z","title":"Exploiting anti-monotonicity of multi-label evaluation measures for inducing multi-label rules","venue":null,"work_id":"40b37dbd-aeac-4a24-9738-b3880cd137a5","year":2018},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.394359Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:f7efeb8e4b3a418407202a94872169c0b93b0f599b57b20ee17d84671a097fca","observation_id":"57f80683-2273-44d1-8d57-a5dcafc1d305","resolution":{"observed_at":"2026-08-14T12:42:51.469990Z","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":"2026-08-14T12:42:51.448636Z","title":"Multiple labels associative classiﬁ- cation","venue":null,"work_id":"05bf0ad8-9b66-44ac-b5f0-1b98d9323481","year":2006},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.398710Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:c9ad63f9baa7496f9cf6fe98e4965377b67426b3bf38c4cf1edf57a6b9ecdaf7","observation_id":"145cda0f-b960-4ab1-93c8-168ef96b67ee","resolution":{"observed_at":"2026-08-14T12:42:51.454096Z","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":"2026-08-14T12:42:51.432509Z","title":"Mining multi-label data","venue":null,"work_id":"21b7d52b-92db-48dc-bc9c-e8c4fbe12d6e","year":2009},"citing_paper":{"arxiv_id":"1908.06874","last_updated":"2019-08-19T15:22:23Z","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:42:51.403085Z"},"links":{"citing_paper":"/paper/1908.06874"},"observation_digest":"sha256:068ec47d7f569c90d4d22b1a4ada29611d666ac8699994ca5b6896b626c4e7c2","observation_id":"acbb906e-db86-437a-8f4a-298f5306fd86","resolution":{"observed_at":"2026-08-14T12:42:51.438130Z","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":"1908.06874","last_updated":"2019-08-19T15:22:23Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T02:24:22.437366Z","submitted_at":"2019-08-19T15:22:23Z","title":"Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning"},"reference_resolution":{"displayed":14,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":14},"total_outbound_references":14},"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 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:1908.06874."}