{"id":"W6938892686","doi":"10.6068/dp14ba81f1b7594","title":"Most Recent Data (2012). Statistics Canada. CANSIM: Health - Disability | Country: Canada | Table: Neurological conditions in institutions, by age, sex, and number of residents | Variable: 18 and over, Spina bifida, Both sexes, 50 residents or more | Units: #, 2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-109.","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; Summary statistics; Health statistics; Economic statistics; Official statistics; Socioeconomic status; Mental health; Medical 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":[0.002621046,0.002512288,0.003113345,0.008089486,0.003647839,0.005392219,0.005467063,0.001940852,0.1514275],"category_scores_gemma":[0.02704643,0.002031473,0.002584212,0.04420893,0.000776962,0.002801409,0.00277381,0.003491183,0.07668694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05928954,"about_ca_system_score_gemma":0.1536988,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9941037,"about_ca_topic_score_gemma":0.9915194,"domain_scores_codex":[0.9947038,0.0003309569,0.000687823,0.0006061384,0.002531708,0.001139485],"domain_scores_gemma":[0.948018,0.002416923,0.001377642,0.001362473,0.04447509,0.002349933],"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":[0.00002079592,0.000006196676,0.0006131019,0.0002840378,0.00001561316,0.000005022846,0.0000154781,0.00008456612,0.000007013235,0.0002217282,0.997449,0.001277477],"study_design_scores_gemma":[0.000257029,0.00001408042,0.02169552,0.001355383,0.00008515934,0.00002845295,0.0004323804,0.0003994406,0.0001511143,0.000708127,0.9747595,0.0001138375],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002810036,0.00004296345,0.00001545565,0.0001316329,0.0000246372,0.00001406068,0.9988626,0.00004985772,0.0008306677],"genre_scores_gemma":[0.0007335737,0.0003646842,0.0004315578,0.000281962,0.00002278735,0.0001626647,0.9937714,0.0001425677,0.004088866],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1514275,"threshold_uncertainty_score":0.5065755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04969401828805619,"score_gpt":0.3201585499567322,"score_spread":0.270464531668676,"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."}}