{"id":"W3157790066","doi":"","title":"Did Weber Affect the Timeliness of Arbitration","year":2016,"lang":"en","type":"article","venue":"","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Jurisdiction; Arbitration; Scope (computer science); Supreme court; Subject-matter jurisdiction; Law; Business; Affect (linguistics); Political science; Law and economics; Original jurisdiction; Sociology; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02190534,0.0001549343,0.0004960948,0.001665101,0.001848234,0.005482797,0.0009217682,0.001472567,0.00893594],"category_scores_gemma":[0.2070038,0.0004155692,0.0005665127,0.001424929,0.004010493,0.005752157,0.001475881,0.002010579,0.0009811579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004956835,"about_ca_system_score_gemma":0.003734721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01852441,"about_ca_topic_score_gemma":0.01822508,"domain_scores_codex":[0.9907933,0.002150079,0.0008036994,0.001499948,0.00285087,0.00190208],"domain_scores_gemma":[0.8584847,0.09348201,0.03156275,0.006782034,0.006618468,0.003069923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.002256869,0.0003303182,0.3760105,0.0002948428,0.0003203417,0.001078133,0.01248884,0.01387734,0.003788518,0.4882315,0.007626715,0.09369608],"study_design_scores_gemma":[0.0003463021,0.0008307168,0.5771576,0.0004237753,0.0003170611,0.001139007,0.01502578,0.01827424,0.01151432,0.2909514,0.08363961,0.000380253],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9232996,0.001095696,0.007473603,0.005037002,0.0002049602,0.0001089106,0.0002453595,0.00006957157,0.06246534],"genre_scores_gemma":[0.9971815,0.0001069205,0.0004972591,0.00009885469,0.00004890214,0.00001228754,0.0000283988,0.00001594652,0.002009919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02190534,"threshold_uncertainty_score":0.1158479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02621969075535529,"score_gpt":0.2118431088312028,"score_spread":0.1856234180758475,"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."}}