{"id":"W2990889257","doi":"10.3917/rindu1.201.0053","title":"Big Data , GAFA et assurance","year":2020,"lang":"fr","type":"article","venue":"Annales des Mines - Réalités industrielles","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Humanities; Political science; Art","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":[0.01584574,0.0006908512,0.0009156604,0.005839404,0.002708849,0.01403558,0.001168642,0.003438008,0.009183301],"category_scores_gemma":[0.03905287,0.0004283436,0.0006650083,0.01124727,0.009797574,0.01750406,0.004447674,0.004586808,0.001637491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006912707,"about_ca_system_score_gemma":0.005712528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01468653,"about_ca_topic_score_gemma":0.00675611,"domain_scores_codex":[0.987382,0.005765475,0.0007371451,0.001286216,0.004031202,0.0007979436],"domain_scores_gemma":[0.9599034,0.0240551,0.003503314,0.004929956,0.005275122,0.002333128],"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":[0.00009721399,0.00003117606,0.005480421,0.0007174556,0.00005814065,0.0001010365,0.001147689,0.00128123,0.0001675875,0.8339226,0.04752805,0.1094675],"study_design_scores_gemma":[0.00002249251,0.00005224999,0.004587641,0.0009573906,0.00002727021,0.0002714575,0.002352738,0.005183998,0.0003379093,0.647883,0.3382508,0.00007295313],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03305169,0.1843806,0.08165011,0.4641116,0.008326448,0.0002225975,0.004574616,0.001706702,0.2219756],"genre_scores_gemma":[0.8037432,0.08434811,0.04260461,0.02447553,0.008434256,0.0004089708,0.002637292,0.0004057151,0.0329424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01584574,"threshold_uncertainty_score":0.08380133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7802436386439482,"score_gpt":0.3783573914606666,"score_spread":0.4018862471832816,"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."}}