{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:3EGBLLXN67HUFRG74GFB7JYRFH","short_pith_number":"pith:3EGBLLXN","schema_version":"1.0","canonical_sha256":"d90c15aeedf7cf42c4dfe18a1fa71129ea49f22a547d31e80a7673816dda7713","source":{"kind":"arxiv","id":"2412.02528","version":1},"attestation_state":"computed","paper":{"title":"Bias Analysis of AI Models for Undergraduate Student Admissions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Kelly Van Busum, Shiaofen Fang","submitted_at":"2024-12-03T16:21:37Z","abstract_excerpt":"Bias detection and mitigation is an active area of research in machine learning. This work extends previous research done by the authors to provide a rigorous and more complete analysis of the bias found in AI predictive models. Admissions data spanning six years was used to create an AI model to determine whether a given student would be directly admitted into the School of Science under various scenarios at a large urban research university. During this time, submission of standardized test scores as part of an application became optional which led to interesting questions about the impact o"},"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":"2412.02528","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-12-03T16:21:37Z","cross_cats_sorted":[],"title_canon_sha256":"4b4e9764bda46bb349a6203c30f600f1587d92b5953857ebe6df006edbeea8b3","abstract_canon_sha256":"92d795b4d23ce46fbedf273dcaf75c0c02a65a3b4846541efb9ce445a7123e09"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:43:51.282023Z","signature_b64":"Z7agGaCh7Nu2X/HjA7nd6ARA1qOx0FB+3rFernBFsywMsvXGeLfJ29gtkDIEBG3w7GrESE1DshIY38S2ss9JCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d90c15aeedf7cf42c4dfe18a1fa71129ea49f22a547d31e80a7673816dda7713","last_reissued_at":"2026-07-05T09:43:51.281558Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:43:51.281558Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bias Analysis of AI Models for Undergraduate Student Admissions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Kelly Van Busum, Shiaofen Fang","submitted_at":"2024-12-03T16:21:37Z","abstract_excerpt":"Bias detection and mitigation is an active area of research in machine learning. This work extends previous research done by the authors to provide a rigorous and more complete analysis of the bias found in AI predictive models. Admissions data spanning six years was used to create an AI model to determine whether a given student would be directly admitted into the School of Science under various scenarios at a large urban research university. During this time, submission of standardized test scores as part of an application became optional which led to interesting questions about the impact o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.02528","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/2412.02528/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":"2412.02528","created_at":"2026-07-05T09:43:51.281617+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.02528v1","created_at":"2026-07-05T09:43:51.281617+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.02528","created_at":"2026-07-05T09:43:51.281617+00:00"},{"alias_kind":"pith_short_12","alias_value":"3EGBLLXN67HU","created_at":"2026-07-05T09:43:51.281617+00:00"},{"alias_kind":"pith_short_16","alias_value":"3EGBLLXN67HUFRG7","created_at":"2026-07-05T09:43:51.281617+00:00"},{"alias_kind":"pith_short_8","alias_value":"3EGBLLXN","created_at":"2026-07-05T09:43:51.281617+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/3EGBLLXN67HUFRG74GFB7JYRFH","json":"https://pith.science/pith/3EGBLLXN67HUFRG74GFB7JYRFH.json","graph_json":"https://pith.science/api/pith-number/3EGBLLXN67HUFRG74GFB7JYRFH/graph.json","events_json":"https://pith.science/api/pith-number/3EGBLLXN67HUFRG74GFB7JYRFH/events.json","paper":"https://pith.science/paper/3EGBLLXN"},"agent_actions":{"view_html":"https://pith.science/pith/3EGBLLXN67HUFRG74GFB7JYRFH","download_json":"https://pith.science/pith/3EGBLLXN67HUFRG74GFB7JYRFH.json","view_paper":"https://pith.science/paper/3EGBLLXN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.02528&json=true","fetch_graph":"https://pith.science/api/pith-number/3EGBLLXN67HUFRG74GFB7JYRFH/graph.json","fetch_events":"https://pith.science/api/pith-number/3EGBLLXN67HUFRG74GFB7JYRFH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3EGBLLXN67HUFRG74GFB7JYRFH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3EGBLLXN67HUFRG74GFB7JYRFH/action/storage_attestation","attest_author":"https://pith.science/pith/3EGBLLXN67HUFRG74GFB7JYRFH/action/author_attestation","sign_citation":"https://pith.science/pith/3EGBLLXN67HUFRG74GFB7JYRFH/action/citation_signature","submit_replication":"https://pith.science/pith/3EGBLLXN67HUFRG74GFB7JYRFH/action/replication_record"}},"created_at":"2026-07-05T09:43:51.281617+00:00","updated_at":"2026-07-05T09:43:51.281617+00:00"}