{"id":"W6920683275","doi":"10.6068/dp14ba83dafaf12","title":"Most Recent Data (2012). Statistics Canada. CANSIM: Health - Health Care Services | Country: Canada | Table: Neurological conditions in institutions, by age, sex, and number of residents | Variable: 45 to 64 years, Brain injury, Females, 50 residents or more | Units: #, 2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-112.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health care; Health statistics; Census; Socioeconomic status; Official statistics; Medical statistics; Economic statistics; Medical prescription; Summary 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":[0.002811352,0.00261964,0.003174268,0.008377245,0.003640953,0.005293103,0.00557892,0.001937357,0.1383311],"category_scores_gemma":[0.02897505,0.001892725,0.002659355,0.04480107,0.0007351941,0.002529131,0.002679536,0.003501347,0.0684092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06201654,"about_ca_system_score_gemma":0.1521321,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9941606,"about_ca_topic_score_gemma":0.9919131,"domain_scores_codex":[0.9946052,0.0003762532,0.0007162269,0.000613767,0.002501195,0.001187346],"domain_scores_gemma":[0.9487703,0.002560069,0.001440528,0.001379424,0.04332514,0.002524413],"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":[0.00001992343,0.000005899458,0.000601278,0.0002688515,0.00001554766,0.000004329633,0.00001442187,0.00008214872,0.000005625503,0.0002025326,0.9976656,0.001113732],"study_design_scores_gemma":[0.0002887355,0.0000159956,0.02404272,0.001451731,0.00009314147,0.00002856337,0.0004848863,0.0004767833,0.0001423622,0.0007623966,0.9720975,0.0001152525],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002888416,0.00004238892,0.00001327575,0.0001365485,0.00002299927,0.00001424525,0.9990011,0.00004118592,0.0006994035],"genre_scores_gemma":[0.0007456141,0.0003050853,0.0003620636,0.0002661573,0.00002359902,0.000167206,0.994671,0.0001072544,0.003352086],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1383311,"threshold_uncertainty_score":0.4627636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0469892876554404,"score_gpt":0.3314658891334625,"score_spread":0.2844766014780221,"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."}}