{"id":"W2560130696","doi":"10.2139/ssrn.2876942","title":"The Supreme Court's Aboriginal Rights Cases & Canada's Resource Industries: Estimating the Economic Effects","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Supreme court; Resource (disambiguation); Promotion (chess); Natural resource; Business; Economics; Law; Political science; Politics","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":[0.004300239,0.0004638039,0.0007081804,0.003225551,0.004868235,0.004574012,0.002378399,0.001964743,0.007672566],"category_scores_gemma":[0.02824551,0.0005223794,0.0007341047,0.0054443,0.002010266,0.001503118,0.001533838,0.00411624,0.0005523012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04466832,"about_ca_system_score_gemma":0.05275497,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9925429,"about_ca_topic_score_gemma":0.9943337,"domain_scores_codex":[0.9968822,0.0006720088,0.0000978496,0.0002531293,0.001077275,0.001017635],"domain_scores_gemma":[0.9816031,0.01180239,0.001764761,0.0004807342,0.00289164,0.001457551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005669002,0.0007177958,0.7156371,0.0002961936,0.0006802627,0.0009398612,0.003887158,0.06939229,0.0002324274,0.0977154,0.06564596,0.04428859],"study_design_scores_gemma":[0.0002038802,0.0001978751,0.7947891,0.000289651,0.001031634,0.0001610938,0.01516073,0.1187188,0.0009975911,0.02136248,0.04695649,0.0001306508],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9369453,0.001428221,0.00150144,0.005213269,0.0000669367,0.0001873201,0.007596131,0.000045654,0.04701577],"genre_scores_gemma":[0.9771866,0.0008941304,0.0008535726,0.0003959417,0.00005370557,0.00005795985,0.003157224,0.00001837545,0.01738259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04466832,"threshold_uncertainty_score":0.3240929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01114501216043423,"score_gpt":0.2142525882654331,"score_spread":0.2031075761049988,"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."}}