{"id":"W4403116494","doi":"10.57745/p0khag","title":"Insurance dataset","year":2024,"lang":"en","type":"other","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001339686,0.001110469,0.0007780652,0.003492849,0.0008477733,0.001806349,0.001930845,0.002153543,0.02598391],"category_scores_gemma":[0.007472686,0.0003101459,0.001190735,0.004973713,0.0003139276,0.001065738,0.00143411,0.001615696,0.02114766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001325547,"about_ca_system_score_gemma":0.002385959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02004981,"about_ca_topic_score_gemma":0.03360954,"domain_scores_codex":[0.998611,0.000261028,0.0002047083,0.0003077055,0.000456238,0.0001591884],"domain_scores_gemma":[0.9974543,0.0008727531,0.0002682215,0.0005121795,0.0006509967,0.0002414204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002075521,0.000163747,0.008317746,0.0006596853,0.0001137417,0.000126113,0.0000550103,0.001396109,0.0003478439,0.002177397,0.9746976,0.01173749],"study_design_scores_gemma":[0.0003520984,0.00007016869,0.02463244,0.0003187756,0.00008403332,0.0003608848,0.0002110867,0.0036503,0.0007473408,0.003105394,0.9664138,0.00005372749],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002648508,0.0002793765,0.0003375251,0.0002724564,0.00005300488,0.00005415649,0.9935043,0.0003650972,0.002485553],"genre_scores_gemma":[0.002154205,0.00009402367,0.0007437853,0.0001097869,0.00001225176,0.00008502622,0.9959401,0.00002693911,0.0008338588],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02598391,"threshold_uncertainty_score":0.08692479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07562978095177517,"score_gpt":0.3188520873582011,"score_spread":0.2432223064064259,"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."}}