{"schema":"https://pith.science/schemas/pith-integrity/v1.json","pith_number":"2607.18568","arxiv_id":"2607.18568","integrity":{"available":true,"endpoint":"/pith/2607.18568/integrity.json","summary":{"critical":1,"advisory":3,"informational":0,"by_detector":{"doi_compliance":{"total":4,"critical":1,"advisory":3,"informational":0}}},"clean":false,"detectors_run":[{"name":"doi_title_agreement","version":"1.0.0","status":"completed","ran_at":"2026-08-03T21:38:47.345457Z","findings_count":0},{"name":"doi_compliance","version":"1.1.0","status":"completed","ran_at":"2026-08-03T15:31:34.568955Z","findings_count":4},{"name":"ai_meta_artifact","version":"1.0.0","status":"skipped","ran_at":"2026-07-29T08:11:49.770722Z","findings_count":0},{"name":"claim_evidence","version":"1.0.0","status":"completed","ran_at":"2026-07-28T16:33:09.102659Z","findings_count":0},{"name":"citation_quote_validity","version":"0.1.0","status":"skipped","ran_at":"2026-07-22T21:57:25.637495Z","findings_count":0},{"name":"cited_work_retraction","version":"1.0.0","status":"completed","ran_at":"2026-07-22T13:52:22.556701Z","findings_count":0}],"findings":[{"detector":"doi_compliance","finding_type":"unresolvable_identifier","severity":"critical","verdict_class":"cross_source","note":"Identifier '10.1162/089976' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","detected_doi":"10.1162/089976","detected_arxiv_id":null,"ref_index":18,"audited_at":"2026-08-01T15:09:33.298394Z"},{"detector":"doi_compliance","finding_type":"recoverable_identifier","severity":"advisory","verdict_class":"incontrovertible","note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.25080/gerudo-f2bc6f59-001) was visible in the surrounding text but could not be confirmed against doi.org as printed.","detected_doi":"10.25080/gerudo-f2bc6f59-001","detected_arxiv_id":null,"ref_index":44,"audited_at":"2026-08-01T15:09:33.298394Z"},{"detector":"doi_compliance","finding_type":"recoverable_identifier","severity":"advisory","verdict_class":"incontrovertible","note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1088/1741-2552/ad38db) was visible in the surrounding text but could not be confirmed against doi.org as printed.","detected_doi":"10.1088/1741-2552/ad38db","detected_arxiv_id":null,"ref_index":19,"audited_at":"2026-08-01T15:09:33.298394Z"},{"detector":"doi_compliance","finding_type":"recoverable_identifier","severity":"advisory","verdict_class":"incontrovertible","note":"DOI is split by whitespace or line breaks in the printed bibliography. Reconstructed DOI 10.1016/j.neuroimage.2018.08.001 resolves to 'Modeling brain dynamic state changes with adaptive mixture independent component analysis'. A reader following the printed text alone cannot reach it.","detected_doi":"10.1016/j.neuroimage.2018.08.001","detected_arxiv_id":null,"ref_index":38,"audited_at":"2026-08-01T15:09:33.298394Z"}],"snapshot_sha256":"80605e4f5c3d7ae0b017bdcdfbf874fb6f65c31f75fbbd32a6bb28a708913b4c"},"events":[{"event_id":16036,"event_type":"pith.integrity.v1","payload_sha256":"546c071d98b7272243f25ce52e2074a21bd1df67b909b3143f9b52b7b723eb3c","signature_b64":"+m3VR4qhuC3eeYrffrbk5i+p+J0feIzR6w1756v8PErHRMfiEP7WeW4uu7VnnfURCGN9TXTVUPM/Gp6FFFYuDQ==","signing_key_id":"pith-v1-2026-05","created_at":"2026-08-01T15:13:33.018753+00:00","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.25080/gerudo-f2bc6f59-001) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"Aaron Meurer, Athan Reines, Ralf Gommers, Y ao-Lung Fang, John Kirkham, Matthew Barber, Stephan Hoyer, Andreas Müller, Sheng Zha, Saul Shanabrook, Stephannie Gacha, Mario Lezcano-Casado, Thomas Fan, T yler Reddy, Alexandre Passos, Hyukjin K","arxiv_id":"2607.18568","detector":"doi_compliance","evidence":{"ref_index":44,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"10.25080/gerud","reconstructed_doi":"10.25080/gerudo-f2bc6f59-001"},"severity":"advisory","ref_index":44,"audited_at":"2026-08-01T15:09:33.298394Z","event_type":"pith.integrity.v1","detected_doi":"10.25080/gerudo-f2bc6f59-001","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"ce0a01154f3f52f5b086eea7a0d00c260695d344b681a4c1a3aff913fc5fe5f5","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null}},{"event_id":16035,"event_type":"pith.integrity.v1","payload_sha256":"3476ace2f60143d99c6824ba76086a090dd96ab084e5dd9ecc107ae8226d0276","signature_b64":"LcyDkF24zTbushCMQEdNlOX5MzB2M102XA7DRUUusAyoXBSclsoPOvol16hqtsjpat0MG85SuIP0pZnGasDnDQ==","signing_key_id":"pith-v1-2026-05","created_at":"2026-08-01T15:13:32.578276+00:00","payload":{"note":"DOI is split by whitespace or line breaks in the printed bibliography. Reconstructed DOI 10.1016/j.neuroimage.2018.08.001 resolves to 'Modeling brain dynamic state changes with adaptive mixture independent component analysis'. A reader following the printed text alone cannot reach it.","snippet":"Sheng-Hsiou Hsu, Luca Pion-Tonachini, Jason Palmer, Makoto Miyakoshi, Scott Makeig, and Tzyy-Ping Jung. Modeling brain dynamic state changes with adaptive mixture independent component analysis. NeuroImage, 183:47–61, 2018. ISSN 10538119. d","arxiv_id":"2607.18568","detector":"doi_compliance","evidence":{"ref_index":38,"verdict_class":"incontrovertible","resolved_title":"Modeling brain dynamic state changes with adaptive mixture independent component analysis","printed_excerpt":"10.1016/j.ne","reconstructed_doi":"10.1016/j.neuroimage.2018.08.001"},"severity":"advisory","ref_index":38,"audited_at":"2026-08-01T15:09:33.298394Z","event_type":"pith.integrity.v1","detected_doi":"10.1016/j.neuroimage.2018.08.001","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"19e02a4542f0138ca142fd31aa19daac48055a0af2c0ea2f625658e3dd77218e","paper_version":1,"verdict_class":"incontrovertible","resolved_title":"Modeling brain dynamic state changes with adaptive mixture independent component analysis","detector_version":"1.1.0","detected_arxiv_id":null}},{"event_id":16034,"event_type":"pith.integrity.v1","payload_sha256":"b4a0035165fd8f0138699c622f6d8c444b5a3b4158c2f6548805c258a8f31fd1","signature_b64":"aZr80f+EIMZm0BfUh9V4Bf8DVg61HFq8+Qn1Nm67imtjv3RdL5G89hSNgyQn1I65LSfrPE19CBAdcy3W3oexAA==","signing_key_id":"pith-v1-2026-05","created_at":"2026-08-01T15:13:32.163144+00:00","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1088/1741-2552/ad38db) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"Nicole Ille. Orthogonal extended infomax algorithm. Journal of Neural Engineering , 21(2), 2024. ISSN 1741-2552. doi: 10.1088/1741 -2552/ad38db","arxiv_id":"2607.18568","detector":"doi_compliance","evidence":{"ref_index":19,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"10.1088/1741","reconstructed_doi":"10.1088/1741-2552/ad38db"},"severity":"advisory","ref_index":19,"audited_at":"2026-08-01T15:09:33.298394Z","event_type":"pith.integrity.v1","detected_doi":"10.1088/1741-2552/ad38db","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"6314bea4c539501234d6e3dcbfe088bbcb56331e0b0d3d341a4f2cfd1b8134ef","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null}},{"event_id":16033,"event_type":"pith.integrity.v1","payload_sha256":"16cd4e3f74ebbcdb81d826c4ddbde70a1e25e47d021883ac8a63d9ba3eb0682e","signature_b64":"N/sGRtVCEwkIU/bVbUZL66Fmk52XxHOEKqu2HZHz+7YhYQyrVueXxEyhYZeGJ+QgHRsIX0x0HH4KI2FaRX8tDQ==","signing_key_id":"pith-v1-2026-05","created_at":"2026-08-01T15:13:31.819711+00:00","payload":{"note":"Identifier '10.1162/089976' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Te-Won Lee, Mark Girolami, and Terrence J. Sejnowski. Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources. Neural Computation, 11(2):417–441, 1999. ISSN 0899-7667, 1530-888X. do","arxiv_id":"2607.18568","detector":"doi_compliance","evidence":{"doi":"10.1162/089976","arxiv_id":null,"ref_index":18,"raw_excerpt":"Te-Won Lee, Mark Girolami, and Terrence J. Sejnowski. Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources. Neural Computation, 11(2):417–441, 1999. ISSN 0899-7667, 1530-888X. doi: 10.1162/089976 699300016719. URL https://direct.mit.edu/neco/article/11/2/417-441/6242","parse_status":"well_formed","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"],"resolution_status":"hard_miss"},"severity":"critical","ref_index":18,"audited_at":"2026-08-01T15:09:33.298394Z","event_type":"pith.integrity.v1","detected_doi":"10.1162/089976","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"5626e72f05d3d2422a19c3075a4facb101436f14a63ddeeb96a41b7dc12d720f","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null}}],"endpoint_self":"/pith/2607.18568/integrity.json","protocol_url":"https://pith.science/pith-integrity-protocol"}