{"schema":"https://pith.science/schemas/pith-integrity/v1.json","pith_number":"2605.01024","arxiv_id":"2605.01024","integrity":{"available":true,"endpoint":"/pith/2605.01024/integrity.json","summary":{"critical":0,"advisory":1,"informational":0,"by_detector":{"doi_compliance":{"total":1,"critical":0,"advisory":1,"informational":0}}},"clean":false,"detectors_run":[{"name":"ai_meta_artifact","version":"1.0.0","status":"completed","ran_at":"2026-05-20T18:39:41.407896Z","findings_count":0},{"name":"doi_compliance","version":"1.0.0","status":"completed","ran_at":"2026-05-19T17:41:53.956956Z","findings_count":1}],"findings":[{"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 (10.5555/3104482.3104569Multimodal) was visible in the surrounding text but could not be confirmed against doi.org as printed.","detected_doi":"10.5555/3104482.3104569Multimodal","detected_arxiv_id":null,"ref_index":20,"audited_at":"2026-05-19T17:41:53.956956Z"}],"snapshot_sha256":"c6037fa1295326af511ddd4397cafc5626cb5bf7788895f271e3156058e789f7"},"events":[{"event_id":2304,"event_type":"pith.integrity.v1","payload_sha256":"df1775661fee95e89af9d3c41aeb5fa69221ea4295765a2df7d97526ce527db0","signature_b64":"Syyepf3zQF9GaG4NDSDVzqj0Twn5KsXaie7vfBfjALIpPNTiFTDOyMEVoALRW5cwJdXBKq7c/FZT2EqPEA1OAg==","signing_key_id":"pith-v1-2026-05","created_at":"2026-05-19T17:42:15.907454+00:00","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.5555/3104482.3104569Multimodal) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"Jiquan Ngiam, Aditya Khosla, Minjae Kim, Juhan Nam, Honglak Lee, and Andrew Y. Ng. 2011. https://dl.acm.org/doi/10.5555/3104482.3104569 Multimodal deep learning . In Proceedings of the 28th International Conference on Machine Learning (ICML","arxiv_id":"2605.01024","detector":"doi_compliance","evidence":{"ref_index":20,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"Jiquan Ngiam, Aditya Khosla, Minjae Kim, Juhan Nam, Honglak Lee, and Andrew Y. Ng. 2011. https://dl.acm.org/doi/10.5555/3104482.3104569 Multimodal deep learning . In Proceedings of the 28th International Conference on Machine Learning (ICML","reconstructed_doi":"10.5555/3104482.3104569Multimodal"},"severity":"advisory","ref_index":20,"audited_at":"2026-05-19T17:41:53.956956Z","event_type":"pith.integrity.v1","detected_doi":"10.5555/3104482.3104569Multimodal","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"7491f95716ee6d52ec1ae331662a063d44df22466f2f0cdef6481b1186a3cb22","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null}}],"endpoint_self":"/pith/2605.01024/integrity.json","protocol_url":"https://pith.science/pith-integrity-protocol"}