{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:AVERFYVA24YWGOVP2LIVQLHYCV","short_pith_number":"pith:AVERFYVA","schema_version":"1.0","canonical_sha256":"054912e2a0d731633aafd2d1582cf815537e79bdba59a8e09fa71d0491a7facf","source":{"kind":"arxiv","id":"2507.19566","version":1},"attestation_state":"computed","paper":{"title":"SLENet: A Novel Multiscale CNN-Based Network for Detecting the Rats Estrous Cycle","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"Hoileong Lee, Qinyang Wang, Xiaodi Pu, Yiming Ma, Yuanming Lai","submitted_at":"2025-07-25T16:20:02Z","abstract_excerpt":"In clinical medicine, rats are commonly used as experimental subjects. However, their estrous cycle significantly impacts their biological responses, leading to differences in experimental results. Therefore, accurately determining the estrous cycle is crucial for minimizing interference. Manually identifying the estrous cycle in rats presents several challenges, including high costs, long training periods, and subjectivity. To address these issues, this paper proposes a classification network-Spatial Long-distance EfficientNet (SLENet). This network is designed based on EfficientNet, specific"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2507.19566","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-07-25T16:20:02Z","cross_cats_sorted":[],"title_canon_sha256":"29a17c8e5754fbae4f51c7fe3a62b0e7acd8b6ff04959c290fd4a51a159ee76d","abstract_canon_sha256":"b24c4ba078806e2c560e9a9438584ee200ba50e00e85e3ee21656423e16821f2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:43:36.673522Z","signature_b64":"V37p4JC8Vhe/Jv/frM7V2wKg8MxuKcT08ddbzSqPNMg2GOtIMnt17JEnSzEENHbLB2ooGHLsvdVdWYmoUDYeAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"054912e2a0d731633aafd2d1582cf815537e79bdba59a8e09fa71d0491a7facf","last_reissued_at":"2026-07-05T11:43:36.673038Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:43:36.673038Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SLENet: A Novel Multiscale CNN-Based Network for Detecting the Rats Estrous Cycle","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"Hoileong Lee, Qinyang Wang, Xiaodi Pu, Yiming Ma, Yuanming Lai","submitted_at":"2025-07-25T16:20:02Z","abstract_excerpt":"In clinical medicine, rats are commonly used as experimental subjects. However, their estrous cycle significantly impacts their biological responses, leading to differences in experimental results. Therefore, accurately determining the estrous cycle is crucial for minimizing interference. Manually identifying the estrous cycle in rats presents several challenges, including high costs, long training periods, and subjectivity. To address these issues, this paper proposes a classification network-Spatial Long-distance EfficientNet (SLENet). This network is designed based on EfficientNet, specific"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.19566","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.19566/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2507.19566","created_at":"2026-07-05T11:43:36.673103+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.19566v1","created_at":"2026-07-05T11:43:36.673103+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.19566","created_at":"2026-07-05T11:43:36.673103+00:00"},{"alias_kind":"pith_short_12","alias_value":"AVERFYVA24YW","created_at":"2026-07-05T11:43:36.673103+00:00"},{"alias_kind":"pith_short_16","alias_value":"AVERFYVA24YWGOVP","created_at":"2026-07-05T11:43:36.673103+00:00"},{"alias_kind":"pith_short_8","alias_value":"AVERFYVA","created_at":"2026-07-05T11:43:36.673103+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/AVERFYVA24YWGOVP2LIVQLHYCV","json":"https://pith.science/pith/AVERFYVA24YWGOVP2LIVQLHYCV.json","graph_json":"https://pith.science/api/pith-number/AVERFYVA24YWGOVP2LIVQLHYCV/graph.json","events_json":"https://pith.science/api/pith-number/AVERFYVA24YWGOVP2LIVQLHYCV/events.json","paper":"https://pith.science/paper/AVERFYVA"},"agent_actions":{"view_html":"https://pith.science/pith/AVERFYVA24YWGOVP2LIVQLHYCV","download_json":"https://pith.science/pith/AVERFYVA24YWGOVP2LIVQLHYCV.json","view_paper":"https://pith.science/paper/AVERFYVA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.19566&json=true","fetch_graph":"https://pith.science/api/pith-number/AVERFYVA24YWGOVP2LIVQLHYCV/graph.json","fetch_events":"https://pith.science/api/pith-number/AVERFYVA24YWGOVP2LIVQLHYCV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AVERFYVA24YWGOVP2LIVQLHYCV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AVERFYVA24YWGOVP2LIVQLHYCV/action/storage_attestation","attest_author":"https://pith.science/pith/AVERFYVA24YWGOVP2LIVQLHYCV/action/author_attestation","sign_citation":"https://pith.science/pith/AVERFYVA24YWGOVP2LIVQLHYCV/action/citation_signature","submit_replication":"https://pith.science/pith/AVERFYVA24YWGOVP2LIVQLHYCV/action/replication_record"}},"created_at":"2026-07-05T11:43:36.673103+00:00","updated_at":"2026-07-05T11:43:36.673103+00:00"}