{"id":"W2295836557","doi":"10.1080/10920277.2000.10595913","title":"“Actuaries at the Dawn of the Computer Age,” James C. Hickman and Linda Heacox, July 1999","year":2000,"lang":"en","type":"article","venue":"North American Actuarial Journal","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Gerontology; History; Art history; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003898702,0.0002581836,0.0004012783,0.0001093591,0.001055721,0.0003075128,0.002425493,0.0000584564,0.00005232978],"category_scores_gemma":[0.00009052551,0.0001498739,0.0001774477,0.0005591802,0.002178212,0.0002538859,0.0006929276,0.0007758864,0.00002748806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001124522,"about_ca_system_score_gemma":0.00020847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002228889,"about_ca_topic_score_gemma":0.0002645034,"domain_scores_codex":[0.9978804,0.0002556751,0.0004825012,0.00034478,0.0005938688,0.0004428005],"domain_scores_gemma":[0.9980073,0.0003438259,0.0005355264,0.0009041781,0.00008418873,0.0001249634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005249598,0.00004297298,0.004283095,0.000004331751,0.00006475469,0.00003138871,0.003085335,0.0005737242,0.00003449965,0.0001872548,0.03243043,0.9592097],"study_design_scores_gemma":[0.0009761781,0.0008381664,0.1923303,0.00006420291,0.00005978349,0.001163131,0.0001118487,0.005770323,0.0003759458,0.001059982,0.7966774,0.0005727994],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798449,0.0003169467,0.0103059,0.007560038,0.001083796,0.0001800648,0.000004511011,0.0001819848,0.0005219046],"genre_scores_gemma":[0.9823518,0.0001399045,0.01535595,0.001350185,0.0005133594,0.000002458569,7.574452e-7,0.00001656503,0.0002690103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9586369,"threshold_uncertainty_score":0.8119861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00778285599729416,"score_gpt":0.2078791977798632,"score_spread":0.200096341782569,"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."}}