{"id":"W6939309197","doi":"10.6068/dp14ba81fff0076","title":"Trend 2000 - 2003. Statistics Canada. CANSIM: Aboriginal People | Country: Canada | Table: Canadian Community Health Survey (CCHS 1.1 and 2.1) off-reserve Aboriginal profile | Variable: Without asthma, Females, Total off-reserve population | Units: , 2000-2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-001.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Official statistics; Population; Socioeconomic status; Population statistics; Economic statistics; Social statistics; Demographic statistics","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":[0.002502406,0.002263981,0.00278198,0.007546124,0.003273999,0.004623506,0.005394534,0.001510993,0.1133224],"category_scores_gemma":[0.01845612,0.001863741,0.002187429,0.03671685,0.0006419595,0.00241094,0.002348707,0.003002745,0.06926697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04759217,"about_ca_system_score_gemma":0.1297767,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9939208,"about_ca_topic_score_gemma":0.9911025,"domain_scores_codex":[0.9963559,0.0003102865,0.0004568127,0.0004968244,0.001592428,0.000787749],"domain_scores_gemma":[0.9731035,0.001104031,0.0008544584,0.001088953,0.0223911,0.001457908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002331639,0.000005005611,0.0006982115,0.0002464122,0.00001951799,0.000006226394,0.00002356954,0.00008760571,0.000008672146,0.0003291381,0.9967546,0.001797805],"study_design_scores_gemma":[0.0001732918,0.00001134345,0.01803998,0.0009943137,0.00007299743,0.00003122399,0.0004270387,0.0004761247,0.0001429354,0.0008335094,0.9787048,0.000092469],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004345423,0.00005275326,0.00003470244,0.0001308832,0.00003523145,0.00002044047,0.9984801,0.00009186593,0.001110578],"genre_scores_gemma":[0.0008315853,0.0003336456,0.0006799369,0.0002263905,0.00002189362,0.0002010962,0.9925638,0.0002095008,0.004932281],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1133224,"threshold_uncertainty_score":0.3791013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03078081616750475,"score_gpt":0.2894635936896904,"score_spread":0.2586827775221856,"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."}}