{"id":"W4252997949","doi":"10.4095/301483","title":"Métis Population, 2006 (by census subdivision)","year":2010,"lang":"en","type":"report","venue":"","topic":"Pacific and Southeast Asian Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Subdivision; Geography; Population; Demography; Archaeology; 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":[0.0003622397,0.000926835,0.000394967,0.003325219,0.000594263,0.0008944631,0.0008940013,0.0003389856,0.02376954],"category_scores_gemma":[0.00296485,0.0003667149,0.0004103974,0.00666287,0.0001247704,0.0007740086,0.0008097339,0.0009665415,0.01969176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001439603,"about_ca_system_score_gemma":0.002713016,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2099488,"about_ca_topic_score_gemma":0.2024221,"domain_scores_codex":[0.9994158,0.00005550328,0.00006892774,0.0000741602,0.0002871729,0.00009848674],"domain_scores_gemma":[0.9990823,0.00004195426,0.0001737581,0.00003554708,0.0005853472,0.00008100108],"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":[0.00006602353,0.00002793691,0.01168372,0.0003438723,0.0000189327,0.00004005148,0.0001539243,0.0002253918,0.0001184921,0.0005077694,0.9738348,0.01297902],"study_design_scores_gemma":[0.0001021075,0.00008892615,0.3456246,0.0003697208,0.0000280325,0.0002502107,0.0008471247,0.0007226001,0.0002284742,0.000268305,0.6514465,0.00002342361],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.009296551,0.0005118516,0.0002122808,0.000397492,0.0002480517,0.0001956053,0.9590884,0.0003425223,0.0297073],"genre_scores_gemma":[0.02917787,0.001824207,0.00203322,0.000351991,0.0001249942,0.001077874,0.9287753,0.0001082525,0.03652639],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7900512,"threshold_uncertainty_score":0.4174535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03763940951933163,"score_gpt":0.352982144518081,"score_spread":0.3153427349987493,"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."}}