{"as_of":"2026-08-18T01:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4d5545171b70e0c60266627ea49509ebd4f3a0380956d2ce483ca5dbbc57c425","coverage":[{"denominator":42,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":42,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T00:14:32.495983Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2608.12269/citation-record","integrity":"/paper/2608.12269/integrity","json":"/paper/2608.12269/citation-record.json","paper":"/paper/2608.12269"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T00:14:33.302973Z","title":"Corruption perceptions index 2024 – ecuador,","venue":null,"work_id":"baa2976c-5cb7-43a2-bac9-772441ee3d71","year":2024},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.285707Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:281cac9a497bceead2b99bc1c6e3e929c212d7f271959874e4fa5a49e6a79313","observation_id":"83b3bba1-5574-46bf-b9ca-0f8a796ec4be","resolution":{"observed_at":"2026-08-16T00:14:33.309256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.285586Z","title":"Informe de Rendi- cion de Cuentas 2024,","venue":null,"work_id":"7c9f1be8-3583-4d5a-b169-17003c109e56","year":2024},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.291838Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:5ae79974d288febc4fde58cf9910fe232527520eab675ca709247b676bed8046","observation_id":"56db6b28-4d22-4b33-8935-ab57a2ba7e20","resolution":{"observed_at":"2026-08-16T00:14:33.291506Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.270336Z","title":"Ecuador design report 2019– 2021,","venue":null,"work_id":"c3a17678-d192-4181-9917-8e16b2876269","year":2019},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.297851Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:986b529f376a79d57d0ad22695aa16ae8a3b22e650f8768fa4b8b462e593e98f","observation_id":"cc3a77d4-1113-4aa1-9e3f-449e4671d0e5","resolution":{"observed_at":"2026-08-16T00:14:33.274966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.255315Z","title":"Towards a methodology for analyzing pub- lic procurement data from kapak’s database,","venue":null,"work_id":"a6daa102-8f06-4c4a-b0a5-0b4e8c661265","year":2024},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.303818Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:02d578188833cf1608c9b1723f02fbd9219907305a8a2f35970c15985b849b74","observation_id":"78b971df-20ab-4281-925f-0736938158b5","resolution":{"observed_at":"2026-08-16T00:14:33.259951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.237417Z","title":"Kapak: Transparency in Public Procurement – Methodology","venue":null,"work_id":"eac17dd9-4a62-4fb9-825a-380a90b0b860","year":2025},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.309251Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:c68286c5e57204a1f431b14fd12d6200b7e8d49669c1fd54018c2452348256b1","observation_id":"049e5f13-cb5a-4c83-8dcf-84d283cd541d","resolution":{"observed_at":"2026-08-16T00:14:33.243058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.222516Z","title":"Deep learning based text classification: A comprehensive review,","venue":null,"work_id":"0dea623e-9a38-4547-80d8-669da602b19a","year":2021},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.314934Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:2934c05ee23fc658d7dc5f570ac48689660c35e42893ee084082fd041d9b21c5","observation_id":"03233528-c3eb-4cbb-ad54-af19d95ef7a4","resolution":{"observed_at":"2026-08-16T00:14:33.227240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.204570Z","title":"Senticnet 3: A common and common-sense knowledge base for cognition-driven sentiment analysis,","venue":null,"work_id":"7b942842-17e9-4ce5-ad82-46b4f01e0f5b","year":2014},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.319956Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:31613141c3698c07e735078dd34c7e56316afc0a30c6d33c4a6a4b47e702986e","observation_id":"d039d670-2793-4462-8aa2-25763045492b","resolution":{"observed_at":"2026-08-16T00:14:33.210654Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.188153Z","title":"Sentiment analysis and topic detection of spanish tweets: A comparative study of nlp techniques,","venue":null,"work_id":"d14641ca-699f-4e8e-96c0-d4f30ddd9ffc","year":2013},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.324381Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:904f598be82cfd1e3933035bf509f20133a55233647b442bf6d8baefc2d16f7c","observation_id":"cbe3e02d-c936-4f62-a738-f030914c8edd","resolution":{"observed_at":"2026-08-16T00:14:33.193872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.167199Z","title":"Clustering of scientific articles using natural language processing,","venue":null,"work_id":"8c1e1bee-cf00-4e48-8301-9ef0df1fe571","year":2022},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.329123Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:47d1eed14714322bbeaa5a9fa946f091b100e0e6ba4f7e27315ec488af3386b7","observation_id":"60368cbb-0ea7-4e5c-961d-08beb675a4f7","resolution":{"observed_at":"2026-08-16T00:14:33.176794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.146590Z","title":"Cluster- ing scientific documents with topic modeling,","venue":null,"work_id":"62c7ed71-2a36-4fe9-a5f2-1b5c534fd337","year":2014},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.333497Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:483d742e83da2314fb2a8e57e14fedf13e6295a18138740e70b10d58b1bd97bd","observation_id":"44e739e5-78ed-4e22-bff7-2dc55bcb9609","resolution":{"observed_at":"2026-08-16T00:14:33.151713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.126032Z","title":"Smart citizen control of public procure- ment in ecuador: Classification of accusatory comments from “sistema oficial de contrataci´ on p´ ublica del ecuador (soce)","venue":null,"work_id":"391d7a87-7642-4b8a-9ed8-1137b09c9bb1","year":2024},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.339265Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:975d8e9d6c40e6bf9e7e7be60f35c70f0959765757c411492deec79b0165a856","observation_id":"758d2a63-fa66-40b7-ae8d-3aa9620b2e98","resolution":{"observed_at":"2026-08-16T00:14:33.132105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.107894Z","title":"Prediction of public procure- ment corruption indices using machine learning methods,","venue":null,"work_id":"28e04f00-08d7-481d-b5b2-e4cff297aa18","year":2019},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.344331Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:234538d12c1d433527e4da9f370d1967cc018ce67e5dec044c8b03e6ace961c0","observation_id":"76e1f738-e05a-4535-9416-97ed67eb608e","resolution":{"observed_at":"2026-08-16T00:14:33.114398Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.090598Z","title":"Generative ai for anti-corruption and integrity in government: Taking stock of promise, perils and practice,","venue":null,"work_id":"482ef9ea-28e6-47ac-aceb-269c03bdafb3","year":2024},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.349893Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:c8ddc4977317474a07e96c2bf84642ae4b2e1907412d6a84be8a9996d542027e","observation_id":"bf665f7e-1f32-4857-80f0-ee4f0307eefd","resolution":{"observed_at":"2026-08-16T00:14:33.097225Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.01478","last_updated":"2022-12-14T20:17:10Z","snapshot_observed_at":"2026-08-16T16:21:27.156086Z","submitted_at":"2022-10-25T01:22:41Z","title":"A machine learning model to identify corruption in M\\'exico's public procurement contracts","version":2},"cited_work":{"arxiv_id":"2211.01478","doi":null,"metadata_source":"pith","pith_arxiv_id":"2211.01478","snapshot_observed_at":"2026-08-16T00:14:32.645900Z","title":"A machine learning model to identify corruption in M\\'exico's public procurement contracts","venue":"cs.CY","work_id":"9d1d408a-a9b4-43d2-88f8-bfd71e78ce2b","year":2022},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.355445Z"},"links":{"cited_paper":"/paper/2211.01478","citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:4a7e4dbcb58fba0fc8fa84cb3f578e3da93428643cf8ad9d689810c98073f163","observation_id":"c14f82dd-8035-4420-951e-b01fc9e77274","resolution":{"observed_at":"2026-08-16T00:14:32.654814Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.072048Z","title":"Survey article: Inter-coder agree- ment for computational linguistics,","venue":null,"work_id":"fdcf350e-7f77-44ad-bea8-f9493a2c20d3","year":2008},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.361663Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:820686f897355999af0562466f10c37fd188b59d2952e675b6c2e6bc5f8ce513","observation_id":"44fe8c61-0d97-45a9-89da-83ac70b7f160","resolution":{"observed_at":"2026-08-16T00:14:33.078500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.054548Z","title":"A review on word embedding tech- niques for text classification,","venue":null,"work_id":"ffbb8d9a-d5d7-49a2-b604-7f19cdae9880","year":2021},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.366039Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:7773505e8ea1a7b2bd0b9ef73d2c31bd74b552d0ca86c9f1f471513b9621c551","observation_id":"e4e2081e-4998-4c1e-ba92-ba47a61868d8","resolution":{"observed_at":"2026-08-16T00:14:33.060435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.035577Z","title":"Llama 3.2-1b","venue":null,"work_id":"81fea089-cfbb-4cb5-84a5-4878ece82581","year":2024},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.370540Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:d949d5b12069f0eccb8c1c2e93446e91240c75322c9830ca3e97399543b819ce","observation_id":"45f2632f-e379-427b-88a3-2829d541a1a9","resolution":{"observed_at":"2026-08-16T00:14:33.042779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.019464Z","title":"Roberta: A robustly optimized bert pretraining approach,","venue":null,"work_id":"6030c585-8ccc-453c-a367-6032d4d99aad","year":null},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.375640Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:0da3af925c3b2eef010b4e82233ef816fa58c2360f918654f5d4524f3302e5b7","observation_id":"6b8f91a3-d1e3-4904-ba43-08d5595571cc","resolution":{"observed_at":"2026-08-16T00:14:33.024183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:33.000968Z","title":"Syntactic-aware text classifi- cation method embedding the weight vectors of feature words,","venue":null,"work_id":"6bef0222-7389-4d7c-aa3a-8e977e8ce484","year":2025},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.380103Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:12a541c11cb68a710b421b5f331c465647a646b25391ebd12fac830954db364d","observation_id":"e7da2e7a-cfaa-424b-8198-8a7bd1984903","resolution":{"observed_at":"2026-08-16T00:14:33.008828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08587","last_updated":"2025-05-11T04:59:46Z","snapshot_observed_at":"2026-08-16T05:43:34.833045Z","submitted_at":"2024-12-11T18:06:44Z","title":"Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.08587","snapshot_observed_at":"2026-08-16T00:14:32.384232Z","title":"Advancing single and multi-task text classification through large language model fine-tuning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.384232Z"},"links":{"cited_paper":"/paper/2412.08587","citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:ffc31a598d5d85c441248eb72ae2493f4fd42e2f0840b034680fc955af096cfb","observation_id":"2303287b-6965-43e5-a6e7-6228f3b8921e","resolution":{"observed_at":"2026-08-16T00:14:32.384232Z","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":"2026-08-16T00:14:32.981919Z","title":"Research on patent text classifi- cation based on word2vec and lstm,","venue":null,"work_id":"07552ef3-c76d-4204-bc62-1e3791c8bb0a","year":2018},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.389105Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:5ca776d5d01622e00d96da6438234ef4c5f19acbcac5efac2535df43d966fc45","observation_id":"3014ccbb-ca76-4588-ba30-57b6b27365be","resolution":{"observed_at":"2026-08-16T00:14:32.987123Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.959412Z","title":"Support vector machines and word2vec for text classification with semantic features,","venue":null,"work_id":"ab4d0037-683e-4eea-b0db-f6fc14d4a890","year":2015},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.393599Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:807a1fef2f6c3eb6fd8c148de08c15767fce3986a2474a393fb4adbbb9bcb407","observation_id":"fc6ff4aa-a545-4159-80ba-c901becd42a0","resolution":{"observed_at":"2026-08-16T00:14:32.965046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.937153Z","title":"Detection of fraud in public procurement using data-driven methods: a systematic mapping study,","venue":null,"work_id":"d832086e-d148-47da-9d90-3fd1ff63bbd5","year":2025},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.397991Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:2b01b1cb3e25304b48d719b1606dfa253975946809e7e5c7cbd230e36b46919b","observation_id":"67d104cb-6131-47d8-97c1-f699bcad6e7f","resolution":{"observed_at":"2026-08-16T00:14:32.945241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.915615Z","title":"Sentence-bert: Sentence embed- dings using siamese bert-networks,","venue":null,"work_id":"0a518321-416d-48ab-9ebd-2c78f1e513d8","year":2019},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.402717Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:c0fe6299173be4a5d39c5d9220dd1057459d4f450c86081a91809bfc3634ec2a","observation_id":"5b4767ea-9633-4223-9680-37dae7f83811","resolution":{"observed_at":"2026-08-16T00:14:32.922602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.894239Z","title":"Least squares quantization in pcm,","venue":null,"work_id":"6005ac90-6514-4fbc-b663-fe1c3c208984","year":1982},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.407927Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:ec2242ee51d0de70f696530fb7b2802bfa2c86a80a72276382f2475be6e7e3e2","observation_id":"629f67c6-e279-4c4c-9db9-2d0c9b99ad9c","resolution":{"observed_at":"2026-08-16T00:14:32.899048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.878937Z","title":"Gaussian mixture models — scikit-learn 1.4.2 documentation","venue":null,"work_id":"55a481c3-e1c3-490d-832c-bd3c81aa2803","year":2024},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.412476Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:090c2887daa6259106d66fc9fb327aa59a96f6345632aa7a6d7363a2964a9b01","observation_id":"ecc141e5-4f0a-4fe7-b5c9-bdd01bcc754a","resolution":{"observed_at":"2026-08-16T00:14:32.883630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.861229Z","title":"Ebk-means: A clustering tech- nique based on elbow method and k-means in wsn,","venue":null,"work_id":"8817e034-f260-44f5-a99a-6cbdc8a354e3","year":2014},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.417950Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:790e2d67c2e4fcdf2c287c72ccea43cf7ab6b980932d3ec84bdc3405b254a4bb","observation_id":"5da3ea14-16b6-493f-9a63-bb24353d55e1","resolution":{"observed_at":"2026-08-16T00:14:32.866500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.842841Z","title":"Silhouettes: A graphical aid to the interpre- tation and validation of cluster analysis,","venue":null,"work_id":"6983b9aa-4207-42bb-85a6-5bc01df1b4ab","year":1987},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.423196Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:de94e1edde86f9df9a95014422fd0e366ee5dc69df90994b5537fd5b04416918","observation_id":"481928f8-f52e-4dc5-a7b7-34b197363541","resolution":{"observed_at":"2026-08-16T00:14:32.848240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.825759Z","title":"Word embedding based clustering to detect topics in social media,","venue":null,"work_id":"570db587-3c2b-4a8e-aef5-b72888105879","year":2019},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.427457Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:d3062266b7949868490d6dfba8e054b5a725cd1630afce0604d9fb3c58723be8","observation_id":"3b45e90d-7002-4086-bdac-ce0b6410d69c","resolution":{"observed_at":"2026-08-16T00:14:32.831286Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.432195Z","title":"Smote: Synthetic minority over-sampling technique,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.432195Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:10faa57ed92cc2ece48d6f2b1af22f722e0b1c10bd4ff534d0df4dc570990e60","observation_id":"7593f1b9-7c4a-470c-aeaa-28b125bf07f3","resolution":{"observed_at":"2026-08-16T00:14:32.432195Z","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":"2026-08-16T00:14:32.790335Z","title":"Stratifiedkfold — scikit-learn 1.6.1 documentation,","venue":null,"work_id":"87204a0a-e67f-4ca1-a202-56d06c40d198","year":2025},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.437234Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:7e2a0550024497e4cce22f89fccc06762692d59847189241f1952fee77527048","observation_id":"b4afcf9e-9a05-4e6d-b32a-8f3e71be56f2","resolution":{"observed_at":"2026-08-16T00:14:32.804380Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.442073Z","title":"Random forests,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.442073Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:bb0d7a143717350cd0103883bc84eff80846d30a942344fc91f5cc4a04454678","observation_id":"86bbe226-0872-4445-8e3e-734cb146f0a9","resolution":{"observed_at":"2026-08-16T00:14:32.442073Z","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":"2026-08-16T00:14:32.754796Z","title":"Comparison between multinomial and bernoulli na¨ ıve bayes for text classifi- cation,","venue":null,"work_id":"8c289250-fc0d-4ee8-b68d-aff649833f71","year":2019},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.446640Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:afb1928236fd8f157e1f4cfd6c93d6c69821c17b84082d3321ae9a9420cb207c","observation_id":"aee370bd-71f9-4558-8e47-dd63bdbae060","resolution":{"observed_at":"2026-08-16T00:14:32.760933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.732251Z","title":"Text classification based on multi-word with support vector machine,","venue":null,"work_id":"2d4770ac-7782-44fd-b0dd-256477bd326e","year":2008},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.451110Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:44991a91c03609ea16b0fdb9d9b36c1518d7a3df04320e9fbf1d453af72dea73","observation_id":"0cc8d099-34d1-41fa-9fdf-1f62eef2a05a","resolution":{"observed_at":"2026-08-16T00:14:32.740500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.03144","last_updated":"2023-05-04T20:53:19Z","snapshot_observed_at":"2026-08-16T15:35:31.088777Z","submitted_at":"2023-05-04T20:53:19Z","title":"Influence of various text embeddings on clustering performance in NLP","version":1},"cited_work":{"arxiv_id":"2305.03144","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.03144","snapshot_observed_at":"2026-08-16T00:14:32.602362Z","title":"Influence of various text embeddings on clustering performance in NLP","venue":"cs.LG","work_id":"cf875f5a-7f00-4a94-8f7d-4b15838219fd","year":2023},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.455865Z"},"links":{"cited_paper":"/paper/2305.03144","citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:885686d1fb761e5a41176d14559889592cdec5e9a65685fbe24ce2b9350009bf","observation_id":"40b64aff-c05c-4008-934a-d8f691770243","resolution":{"observed_at":"2026-08-16T00:14:32.610874Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.714772Z","title":"Glove word embedding and dbscan algorithms for semantic document clustering,","venue":null,"work_id":"de493e9f-ad0f-4673-814b-18da6ce7b720","year":2020},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.460871Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:238220c73182c7ebeb0397e83574edbde4df416618029f08aa5f6a7a71f0bc77","observation_id":"27442053-e835-49b3-8f93-2c36c2c6c58c","resolution":{"observed_at":"2026-08-16T00:14:32.719966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.00422","last_updated":"2025-03-20T10:08:31Z","snapshot_observed_at":"2026-08-16T14:30:40.017845Z","submitted_at":"2023-12-31T08:22:51Z","title":"Interpreting the Curse of Dimensionality from Distance Concentration and Manifold Effect","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.00422","snapshot_observed_at":"2026-08-16T00:14:32.464917Z","title":"Interpreting the curse of dimen- sionality from distance concentration and manifold effect,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.464917Z"},"links":{"cited_paper":"/paper/2401.00422","citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:c134d08ea79d5ba8d079de8b5fbdbe1c5da526c2617bc10b873c44197bddab82","observation_id":"a8fd20e6-339d-4fdb-8808-8ef58c35fce4","resolution":{"observed_at":"2026-08-16T00:14:32.464917Z","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":"2026-08-16T00:14:32.699628Z","title":"Beyond words: A comparative analysis of llm embeddings for effective clustering,","venue":null,"work_id":"8af346e8-acbe-4b1a-8528-4a579709fc1c","year":2024},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.472012Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:da6ca7ad541bf02d7db395c7e4fb22bc27e5eca17419775fb48bd3da91aa271d","observation_id":"56556cd4-a214-464a-95c5-e5a36f9193d3","resolution":{"observed_at":"2026-08-16T00:14:32.704166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.682895Z","title":"Text clustering with large language model embeddings,","venue":null,"work_id":"08a3d199-f15a-4505-ab27-a82243e8c0d3","year":2025},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.479621Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:8d62ee8483bb72095b7710e8d8be00a551ca82ac072b01f4eedf9c3d9e07a9c1","observation_id":"6c2def6e-564f-4ad6-8b01-bb204da83836","resolution":{"observed_at":"2026-08-16T00:14:32.687909Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T00:14:32.666480Z","title":"On the sentence embeddings from pre-trained language models,","venue":null,"work_id":"14cae950-78fd-4382-a11a-64f4628e3dc3","year":2020},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.484918Z"},"links":{"citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:c4af6ec8eccd4ed2f77d67db91da3ac6e566bfc489c4b5daa64162c8a89d9a04","observation_id":"170247b7-f926-43b1-ac49-0179c05c20f8","resolution":{"observed_at":"2026-08-16T00:14:32.671471Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.08904","last_updated":"2022-08-05T09:33:10Z","snapshot_observed_at":"2026-08-16T17:20:27.429412Z","submitted_at":"2022-02-17T21:35:56Z","title":"SGPT: GPT Sentence Embeddings for Semantic Search","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.08904","snapshot_observed_at":"2026-08-16T00:14:32.490894Z","title":"Sgpt: Gpt sentence embeddings for semantic search,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.490894Z"},"links":{"cited_paper":"/paper/2202.08904","citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:207c0fbbffc70902b032d24cd36dbf45401811d66fb53e1b88200329a5086005","observation_id":"6dbcc057-de8f-4547-8128-c1ccb812ebf9","resolution":{"observed_at":"2026-08-16T00:14:32.490894Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.05961","last_updated":"2024-08-21T22:46:05Z","snapshot_observed_at":"2026-08-16T14:02:33.067745Z","submitted_at":"2024-04-09T02:51:05Z","title":"LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.05961","snapshot_observed_at":"2026-08-16T00:14:32.495983Z","title":"Llm2vec: Large language mod- els are secretly powerful text encoders,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T00:14:32.495983Z"},"links":{"cited_paper":"/paper/2404.05961","citing_paper":"/paper/2608.12269"},"observation_digest":"sha256:d2275b26475d366ca76c309129ff7c6f567bada943506be5adaae524704e8af5","observation_id":"fc30bb81-5553-4def-8b27-e6403cad9ed3","resolution":{"observed_at":"2026-08-16T00:14:32.495983Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.12269","last_updated":"2026-08-12T17:09:14Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-17T22:34:50.222415Z","submitted_at":"2026-08-12T17:09:14Z","title":"A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement"},"reference_resolution":{"displayed":42,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":2,"verified_fuzzy":34},"total_outbound_references":42},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2608.12269."}