{"id":"W6901635404","doi":"10.6068/dp14ba844a24568","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, Spina bifida, Females, Less than 10 residents | 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; Medical statistics; Official statistics; Medical prescription; Summary statistics; Economic 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":[0.002727202,0.002595413,0.003292084,0.008570457,0.00380367,0.005410476,0.005766022,0.001991921,0.14018],"category_scores_gemma":[0.02803748,0.001930942,0.002674408,0.04482654,0.0007311563,0.002510336,0.0027649,0.003592379,0.06853715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06330214,"about_ca_system_score_gemma":0.1529787,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944119,"about_ca_topic_score_gemma":0.9924853,"domain_scores_codex":[0.9947473,0.0003554921,0.0006912194,0.0006167791,0.002395401,0.00119382],"domain_scores_gemma":[0.951401,0.002504358,0.001390617,0.001324351,0.04086616,0.002513477],"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":[0.00001863889,0.00000571527,0.0006141358,0.0002634165,0.000015447,0.000004500425,0.00001510165,0.00007685843,0.000005422153,0.0002053005,0.9976565,0.001118937],"study_design_scores_gemma":[0.0002896696,0.00001537111,0.02444653,0.001499389,0.00009576453,0.00003088001,0.0005095396,0.0004816732,0.0001386135,0.0007773856,0.9715989,0.0001162815],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002923486,0.0000425392,0.00001312573,0.0001380901,0.00002272991,0.00001367171,0.9989924,0.00003987968,0.0007084165],"genre_scores_gemma":[0.0007517156,0.00031464,0.0003677339,0.000272039,0.00002301693,0.0001683053,0.9945721,0.0001073362,0.003423038],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.14018,"threshold_uncertainty_score":0.4689487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05141266265247844,"score_gpt":0.3177142455780788,"score_spread":0.2663015829256004,"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."}}