{"id":"W4386941243","doi":"10.7202/1091878ar","title":"L’impact de la sinistralité passée sur la sinistralité future (2) : une modélisation des classes de risques","year":2011,"lang":"fr","type":"article","venue":"Assurances et gestion des risques","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"HEC Montréal","keywords":"Humanities; Political science; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002644224,0.0005281208,0.0006735597,0.0003670359,0.0003576947,0.0005863455,0.0003717653,0.0008363128,0.0007103767],"category_scores_gemma":[0.0007881141,0.0006122105,0.0003455197,0.0009723638,0.00119343,0.001912508,0.00004333822,0.0006869271,0.0001077563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006277795,"about_ca_system_score_gemma":0.0002330512,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009655911,"about_ca_topic_score_gemma":0.001223868,"domain_scores_codex":[0.9965103,0.0007923294,0.001095583,0.0006586619,0.0001364979,0.0008065902],"domain_scores_gemma":[0.9975697,0.0007667307,0.0007166378,0.0004297552,0.0002930213,0.0002241303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002004755,0.0008580603,0.6189665,0.0004798928,0.0003622657,0.000055999,0.007717018,0.00290758,0.00009325556,0.3041292,0.01229643,0.05193328],"study_design_scores_gemma":[0.0006157305,0.0003098861,0.8101507,0.0002711222,0.00005657188,0.00009943622,0.0004858769,0.005946986,0.0006777132,0.1225792,0.05818573,0.0006210152],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8832681,0.01088914,0.008638472,0.009180018,0.000837054,0.0002886352,0.0008011615,0.0002773558,0.08582006],"genre_scores_gemma":[0.969905,0.01413269,0.01181856,0.0003383573,0.0004446308,0.00005454417,0.000119044,0.00008049951,0.003106646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1911842,"threshold_uncertainty_score":0.999633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06179296203955696,"score_gpt":0.2936263542049259,"score_spread":0.2318333921653689,"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."}}