{"id":"W2765267238","doi":"","title":"Rewriting Hockey's Unwritten Rules: Moore v. Bertuzzi","year":2017,"lang":"en","type":"article","venue":"Maine law review","topic":"Legal Systems and Judicial Processes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rewriting; Law and economics; Programming language; Law; Computer science; Political science; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.004551639,0.0005054672,0.0003416913,0.001078742,0.01171231,0.007701173,0.003156833,0.01000583,0.006844902],"category_scores_gemma":[0.01679162,0.0007738435,0.0004842553,0.0005388773,0.00784657,0.003630967,0.004076399,0.01458222,0.001699087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01426979,"about_ca_system_score_gemma":0.01415269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3477134,"about_ca_topic_score_gemma":0.4701721,"domain_scores_codex":[0.9946954,0.0008164441,0.0001929505,0.00101716,0.001824124,0.001454053],"domain_scores_gemma":[0.9971151,0.001256632,0.0001538203,0.0002130823,0.0006627351,0.0005984875],"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":[0.00005726095,0.00007061888,0.002271936,0.00007158308,0.00002664985,0.001488717,0.01239738,0.0004626013,0.0004470527,0.5345775,0.4198336,0.0282951],"study_design_scores_gemma":[0.0000518827,0.00008561397,0.004496203,0.0004707302,0.00005366314,0.0005966206,0.005869766,0.0006765066,0.0008085682,0.04340292,0.9433575,0.0001299357],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03961042,0.005324985,0.002892653,0.1682756,0.007027017,0.0001785544,0.0001348126,0.000157832,0.7763982],"genre_scores_gemma":[0.4554127,0.002874038,0.001823415,0.2228876,0.002380911,0.0002772123,0.0001170769,0.0002180507,0.3140091],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3477134,"threshold_uncertainty_score":0.691379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0404144973460183,"score_gpt":0.3595711320834672,"score_spread":0.3191566347374489,"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."}}