{"id":"W6976559774","doi":"10.6068/dp14ba853fd2a27","title":"Most Recent Data (2005). Statistics Canada. CANSIM: Health - Disability | Country: Canada | Table: Canadian Community Health Survey (CCHS 3.1) off-reserve Aboriginal profile, by sex | Variable: Injuries within the past 12 months, Total off-reserve population, Both sexes | Units: , 2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-109.","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; Health statistics; Official statistics; Summary statistics; Economic statistics; Socioeconomic status; Mental health; Community health; General Social Survey","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":[0.002640569,0.002336855,0.00275796,0.007268329,0.003653818,0.004740579,0.005229851,0.001655456,0.1487297],"category_scores_gemma":[0.02285571,0.001913356,0.002215208,0.04116614,0.0006642308,0.002587931,0.002321144,0.003206491,0.08132856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05496185,"about_ca_system_score_gemma":0.1417398,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9938917,"about_ca_topic_score_gemma":0.9906657,"domain_scores_codex":[0.9951532,0.000338414,0.0005965266,0.000537139,0.002363398,0.001011426],"domain_scores_gemma":[0.9603481,0.00177443,0.0009841266,0.001110876,0.03390161,0.001880918],"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":[0.0000155048,0.000005768344,0.0005065774,0.0002062467,0.00001140062,0.000004453785,0.00001539418,0.00007210358,0.00000586144,0.0002179955,0.997615,0.001323735],"study_design_scores_gemma":[0.0001678359,0.00001260258,0.02003716,0.0009846319,0.00006683452,0.00002398048,0.0004421578,0.0003200216,0.0001276576,0.0006217711,0.977108,0.00008729792],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003318353,0.00004397772,0.00002040988,0.0001203628,0.00002795367,0.00001688248,0.9986339,0.00005557115,0.001047792],"genre_scores_gemma":[0.0007290182,0.0003498853,0.0005146041,0.0002421479,0.0000207315,0.0001628952,0.9927683,0.0001429954,0.005069529],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1487297,"threshold_uncertainty_score":0.4975505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03578950667860595,"score_gpt":0.295640461835926,"score_spread":0.25985095515732,"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."}}