{"id":"W4206386309","doi":"10.7202/1023242ar","title":"Arbitration Statistics","year":2014,"lang":"en","type":"article","venue":"Relations industrielles","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arbitration; Statistics; Computer science; Mathematics; Political science; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.01176071,0.0008446195,0.001344467,0.007768983,0.002719081,0.003572874,0.002555291,0.001388606,0.1202463],"category_scores_gemma":[0.0877587,0.0005314028,0.0006344341,0.01505252,0.001168772,0.001461735,0.001416399,0.001964592,0.01793086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01413315,"about_ca_system_score_gemma":0.03849114,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7530013,"about_ca_topic_score_gemma":0.7667262,"domain_scores_codex":[0.984235,0.003958201,0.001417287,0.001571803,0.00721861,0.001599148],"domain_scores_gemma":[0.9166419,0.02020402,0.005564907,0.009060951,0.04542098,0.00310729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001154173,0.00002540609,0.009772318,0.0001833988,0.00004237736,0.00004096846,0.0002164078,0.001372365,0.000083439,0.008063139,0.9280799,0.05200488],"study_design_scores_gemma":[0.0001332621,0.00005115306,0.04921931,0.0003837407,0.00005950565,0.00009217558,0.0004370387,0.008775653,0.0004743768,0.007484808,0.9328117,0.00007721481],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01521118,0.003794202,0.05151244,0.007305924,0.001626026,0.00307731,0.7593404,0.005832631,0.1522998],"genre_scores_gemma":[0.2231813,0.003167273,0.04067139,0.001898592,0.001014862,0.004599653,0.4616425,0.00244678,0.2613775],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7530013,"threshold_uncertainty_score":0.4969067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1077530157886229,"score_gpt":0.3921552847532326,"score_spread":0.2844022689646098,"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."}}