{"id":"W6901644745","doi":"10.6068/dp14ba8565eba61","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: Total, all ages, Huntington's disease, Males, 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; Health policy","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":[0.00279725,0.002658939,0.003239057,0.008605957,0.003838669,0.005526271,0.005777183,0.001938449,0.1397822],"category_scores_gemma":[0.02772667,0.001936747,0.002654435,0.04577551,0.0007322154,0.002547981,0.002811186,0.003483726,0.06795885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06592432,"about_ca_system_score_gemma":0.1569363,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947014,"about_ca_topic_score_gemma":0.9928161,"domain_scores_codex":[0.9945418,0.0003752953,0.0007138159,0.0006196505,0.002528721,0.00122068],"domain_scores_gemma":[0.9500933,0.002500071,0.001384699,0.001318825,0.04208046,0.00262267],"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":[0.00001883547,0.000005705238,0.0005743036,0.000258158,0.00001517797,0.000004398126,0.00001516434,0.00007829475,0.000005430184,0.0002154329,0.9976943,0.001114582],"study_design_scores_gemma":[0.0002726672,0.00001503969,0.02387158,0.0014069,0.00009375741,0.00002860083,0.0004929084,0.0004737958,0.0001399902,0.0007636666,0.9723269,0.0001142301],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002977303,0.00004139604,0.00001368337,0.0001390563,0.00002279488,0.00001444841,0.9989267,0.00004189523,0.0007701249],"genre_scores_gemma":[0.0007502569,0.0003066791,0.0003747577,0.0002664998,0.00002267368,0.0001653126,0.9944554,0.0001094116,0.003549106],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1397822,"threshold_uncertainty_score":0.4783166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03995694422740625,"score_gpt":0.3120305488551286,"score_spread":0.2720736046277223,"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."}}