{"id":"W3136315925","doi":"10.2139/ssrn.3787619","title":"Who Counts? Measuring Disability Cross-Nationally in Census Data","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; University of Toronto","funders":"","keywords":"Census; Geography; Statistics; Demography; Gerontology; Environmental health; Medicine; Population; Sociology; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005563841,0.000342853,0.0005431729,0.002860582,0.0005116194,0.001992135,0.0008935942,0.0006373518,0.002141134],"category_scores_gemma":[0.03769508,0.0004235659,0.0007502657,0.006404267,0.0004449418,0.002865598,0.00215768,0.0009332257,0.0007714928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001166104,"about_ca_system_score_gemma":0.001981498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08215636,"about_ca_topic_score_gemma":0.1399477,"domain_scores_codex":[0.9935197,0.002981749,0.001312399,0.0005383195,0.001059935,0.0005878793],"domain_scores_gemma":[0.9877397,0.003990425,0.004096584,0.001391028,0.002303285,0.0004789809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000226851,0.00005401593,0.9665319,0.0001296947,0.0001953934,0.00001307248,0.0008129786,0.0002082886,0.00004658623,0.001070538,0.00959609,0.02131874],"study_design_scores_gemma":[0.00001469356,0.00004886335,0.9746504,0.0004905448,0.0001731357,0.0001243241,0.0051773,0.001544327,0.000321353,0.001914316,0.01550959,0.00003117261],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8769705,0.002332345,0.007156013,0.006218634,0.0004520189,0.0002385403,0.08083606,0.0001302688,0.02566557],"genre_scores_gemma":[0.965057,0.001065009,0.006561898,0.000659044,0.0001029119,0.0004554449,0.02463691,0.00003653909,0.001425159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08215636,"threshold_uncertainty_score":0.1633563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06606675435594682,"score_gpt":0.3873185180572251,"score_spread":0.3212517637012783,"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."}}