{"id":"W6959683505","doi":"10.11575/prism/34033","title":"Why Age Matters for Young and Old Drivers","year":2006,"lang":"en","type":"other","venue":"PRISM (University of Calgary)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Underwriting; Proxy (statistics); Automobile insurance; Medical underwriting; Insurance policy; Casualty insurance; General insurance; Key person insurance; Realm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001244118,0.0001310251,0.0002937325,0.0008178576,0.001215992,0.001575877,0.0004742599,0.001399105,0.008228009],"category_scores_gemma":[0.00877852,0.0001980078,0.0004226055,0.0006279859,0.0006625241,0.001825811,0.0005606841,0.0007579015,0.001888261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001349103,"about_ca_system_score_gemma":0.00199612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09048992,"about_ca_topic_score_gemma":0.1527924,"domain_scores_codex":[0.9994442,0.00008820357,0.0000304414,0.00008362917,0.0001598512,0.0001935498],"domain_scores_gemma":[0.9970663,0.0005583207,0.0004578026,0.0001116967,0.0009487954,0.0008571141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003382791,0.0001322907,0.845157,0.0001640805,0.00005666036,0.0004323868,0.003967876,0.00009046333,0.0003633229,0.003453553,0.03979057,0.1060535],"study_design_scores_gemma":[0.00002591063,0.0001242147,0.9438931,0.0003107152,0.00010014,0.0006552209,0.01147637,0.0001958582,0.0002883639,0.00575679,0.03713759,0.00003577953],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8643698,0.0249218,0.0004095853,0.06060366,0.001266616,0.00005067222,0.001604769,0.00004030059,0.0467329],"genre_scores_gemma":[0.9778134,0.006716314,0.0001716263,0.004295759,0.0004226069,0.00001189391,0.0003909323,0.00001947389,0.010158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09048992,"threshold_uncertainty_score":0.1799265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007071292267622932,"score_gpt":0.1827448064592778,"score_spread":0.1756735141916549,"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."}}