{"id":"W6901530566","doi":"10.6068/dp14ba83cf06741","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Health - Lifestyle and Social Conditions | Country: Canada | Table: Canadian Community Health Survey (CCHS 2.1) urban-rural profile, by sex | Variable: Good self-rated health, Urban fringe, Both sexes | Units: , 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-114.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Socioeconomic status; Official statistics; Census; Health statistics; Economic statistics; Social statistics; General Social Survey; Summary statistics; Community health","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":[0.002911536,0.002514344,0.003069719,0.007356484,0.004006451,0.004968882,0.005780134,0.001806363,0.1395821],"category_scores_gemma":[0.02582238,0.001922923,0.002444525,0.04398522,0.0007277497,0.002559914,0.002614343,0.003485447,0.08406143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05368577,"about_ca_system_score_gemma":0.128437,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9937103,"about_ca_topic_score_gemma":0.9914185,"domain_scores_codex":[0.9952055,0.0003985822,0.0005973527,0.0005819751,0.002197202,0.001019458],"domain_scores_gemma":[0.9594364,0.002162743,0.001006195,0.001331474,0.03396817,0.002094991],"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":[0.00001636817,0.000005261235,0.0005234324,0.000217226,0.00001179869,0.000004203368,0.00001514751,0.00006892235,0.00000546916,0.0001918995,0.9977546,0.001185644],"study_design_scores_gemma":[0.0002189733,0.00001269102,0.02096095,0.001063983,0.0000745491,0.00002557291,0.0004569577,0.0003851597,0.0001259159,0.0007270795,0.9758487,0.00009943715],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002589126,0.00003663461,0.00001755388,0.0001036569,0.00002182485,0.00001431389,0.999015,0.00004623516,0.0007190204],"genre_scores_gemma":[0.0005986275,0.000261773,0.0004303368,0.0001978676,0.00001692768,0.0001674555,0.9950312,0.0001132415,0.003182612],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1395821,"threshold_uncertainty_score":0.4669486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03632195478713957,"score_gpt":0.2806162560648368,"score_spread":0.2442943012776972,"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."}}