{"id":"W4400332946","doi":"10.1080/01639374.2024.2355734","title":"In Memoriam: Nancy J. Williamson","year":2024,"lang":"en","type":"article","venue":"Cataloging & Classification Quarterly","topic":"Oral History, Memory, Narrative Analysis","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Library science; Philosophy; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002821256,0.0002060311,0.0002375375,0.0004856367,0.0002179318,0.0003327423,0.0002345663,0.00006811052,0.001204584],"category_scores_gemma":[0.00002513117,0.0001914842,0.0001303871,0.0002442667,0.0002569315,0.0008754883,0.000006688661,0.0002556274,0.002016611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002966876,"about_ca_system_score_gemma":0.00008193273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002178989,"about_ca_topic_score_gemma":0.001326052,"domain_scores_codex":[0.9984758,0.00009111407,0.0004249997,0.0005009662,0.0002293392,0.0002777437],"domain_scores_gemma":[0.9992605,0.00008368072,0.00009261986,0.0004039999,0.00009209403,0.00006713848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002301695,0.0001927098,0.0002293775,0.000234493,0.0001009507,0.0001080792,0.2656542,0.000005296357,0.004395504,0.488624,0.1825867,0.05784561],"study_design_scores_gemma":[0.0001737319,0.0001409265,0.0006859874,0.0001130658,0.00004893893,0.000003664437,0.01800782,0.001933754,0.00008803388,0.004706644,0.9737576,0.0003397972],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.46284,0.03084308,0.00557183,0.04914226,0.06478079,0.00269869,0.0005707668,0.004152468,0.3794001],"genre_scores_gemma":[0.9752226,0.00001791763,0.00005013564,0.0002089825,0.001595888,0.00008409633,0.0001721495,0.00003493937,0.02261327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.791171,"threshold_uncertainty_score":0.9997085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04393651848291071,"score_gpt":0.2714010490359206,"score_spread":0.2274645305530099,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}