{"id":"W6976515948","doi":"10.6068/dp14ba80bcf9753","title":"Most Recent Data (2010). Statistics Canada. CANSIM: Languages | Country: Canada | Table: Health indicator profile, by linguistic characteristic (mother tongue, first official language spoken) | Variable: High blood pressure, Total, mother tongue, Both sexes | Units: %, 2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-148.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Official statistics; Economic statistics; Census; Population; Socioeconomic status; Social statistics; First language; Population 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":[0.002429034,0.002502678,0.002911407,0.007852797,0.003638743,0.005402273,0.005211763,0.001701005,0.1263342],"category_scores_gemma":[0.02451379,0.001866062,0.002172886,0.04539197,0.0007631545,0.00265123,0.002635475,0.003314186,0.07158345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0653365,"about_ca_system_score_gemma":0.1646841,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9952967,"about_ca_topic_score_gemma":0.9937232,"domain_scores_codex":[0.9949849,0.0003372622,0.0006012337,0.0006175777,0.002401128,0.001057831],"domain_scores_gemma":[0.9564762,0.002042198,0.001115764,0.001226649,0.0369177,0.002221436],"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":[0.0000218382,0.000006655524,0.0007128286,0.0002762781,0.00001689367,0.000005386437,0.00001950822,0.00009315004,0.00000887545,0.0002518116,0.9971808,0.00140596],"study_design_scores_gemma":[0.0002151679,0.00001319366,0.02230651,0.001052264,0.00008267597,0.00002630251,0.0004817202,0.0004210048,0.0001663188,0.0006546944,0.9744707,0.000109352],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003901113,0.0000483686,0.00001749142,0.0001162801,0.00002409862,0.00001339731,0.9988165,0.00005785106,0.0008670554],"genre_scores_gemma":[0.0008341846,0.0003410322,0.0004412965,0.0002354448,0.00001955551,0.0001539312,0.9932388,0.0001421368,0.004593697],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1263342,"threshold_uncertainty_score":0.4740517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704958028892961,"score_gpt":0.2525927889456046,"score_spread":0.2355432086566749,"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."}}