{"id":"W6920518233","doi":"10.6068/dp14ba80b73e119","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Society and Community - Rural Canada | Country: Canada | Table: Canadian Community Health Survey (CCHS 2.1) urban-rural profile, by sex | Variable: Without high blood pressure, Rural fringe, Females | Units: , 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-189.","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; Rural area; Social statistics; Demographic statistics; Population statistics; American Community 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":[0.002614998,0.002388958,0.002828697,0.008051809,0.004138851,0.005217524,0.005292982,0.001553621,0.1252885],"category_scores_gemma":[0.02164294,0.001891537,0.002099147,0.04770781,0.0007587124,0.002578303,0.002466589,0.003287974,0.07320105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07054934,"about_ca_system_score_gemma":0.1787074,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9963763,"about_ca_topic_score_gemma":0.9942377,"domain_scores_codex":[0.9948606,0.0003517476,0.0005879927,0.0005789106,0.002432282,0.00118848],"domain_scores_gemma":[0.9583656,0.001604289,0.001033032,0.001110098,0.03572177,0.002165159],"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":[0.0000177823,0.000005974319,0.0006855812,0.0002045902,0.00001168796,0.00000547949,0.00002021867,0.00006943421,0.000006486348,0.0002593917,0.9971941,0.001519342],"study_design_scores_gemma":[0.0001545889,0.00001254045,0.02503588,0.0009321062,0.0000655727,0.00002747687,0.0005765472,0.0003386748,0.0001378614,0.0006074691,0.9720212,0.00009006354],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004875995,0.00006520672,0.0000260447,0.000158695,0.00003498072,0.00002079486,0.9981231,0.00006223463,0.001460086],"genre_scores_gemma":[0.001249,0.0005457257,0.0007070871,0.0003254509,0.00002842728,0.0002173923,0.9886092,0.0001939475,0.00812379],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1252885,"threshold_uncertainty_score":0.5118737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04104632548757534,"score_gpt":0.2653121144548137,"score_spread":0.2242657889672384,"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."}}