{"id":"W1601529068","doi":"10.60082/2563-8505.1056","title":"Negotiations with Métis: What Courts Can Do to Help","year":2004,"lang":"en","type":"article","venue":"Supreme Court law review","topic":"Political Systems and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Negotiation; Dispute resolution; Political science; Representation (politics); Dispute mechanism; Identification (biology); Resolution (logic); Law; Law and economics; Alternative dispute resolution; Sociology; Computer science; Politics; Artificial intelligence","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":[0.03824618,0.0007011506,0.001114826,0.003575281,0.01917537,0.02728035,0.004633875,0.02029462,0.01677912],"category_scores_gemma":[0.1133664,0.0006858112,0.0008848929,0.002542665,0.015203,0.03292305,0.01547741,0.01312075,0.003822682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00628997,"about_ca_system_score_gemma":0.01569278,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005777293,"about_ca_topic_score_gemma":0.01038314,"domain_scores_codex":[0.9621344,0.0222703,0.001764117,0.001936925,0.006670731,0.005223553],"domain_scores_gemma":[0.9436068,0.03066299,0.004021176,0.005354902,0.008081651,0.008272529],"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":[0.00004650611,0.0002038662,0.002676339,0.0002426463,0.00003187499,0.0008140682,0.01475846,0.0006089172,0.0003645665,0.7624693,0.1002884,0.1174951],"study_design_scores_gemma":[0.00008373724,0.00006850669,0.0009234734,0.0009345877,0.00002455717,0.0003489231,0.02188613,0.001012283,0.0004548238,0.6058729,0.3683083,0.00008174942],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01735222,0.01198576,0.02596213,0.6223816,0.002588319,0.0002098039,0.00005858582,0.000386082,0.3190755],"genre_scores_gemma":[0.7918062,0.009767462,0.02946668,0.09877296,0.002709583,0.0006075241,0.0001895703,0.0003465669,0.06633363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9942227,"threshold_uncertainty_score":0.2022676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02455703768056568,"score_gpt":0.3077829696692195,"score_spread":0.2832259319886538,"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."}}