{"id":"W4238030428","doi":"10.4095/301488","title":"Sex Composition (male) by Age, 2006 - Youth by Census Subdivision (under 15 years of age)","year":2010,"lang":"en","type":"report","venue":"","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Composition (language); Demography; Subdivision; Geography; Gerontology; Medicine; Sociology; Archaeology; Population; Art","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":[0.0003249482,0.0004007358,0.0002945901,0.00264306,0.0006076872,0.0005758101,0.0006653462,0.0001817134,0.008067126],"category_scores_gemma":[0.00114449,0.0002131548,0.0004651104,0.003355209,0.0001244079,0.0003792397,0.0004531686,0.0003821848,0.004361806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001437911,"about_ca_system_score_gemma":0.002423598,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5537206,"about_ca_topic_score_gemma":0.7110639,"domain_scores_codex":[0.9994959,0.00002697127,0.00004990056,0.00005468721,0.0002506349,0.0001218838],"domain_scores_gemma":[0.9990866,0.00002537715,0.0001573238,0.00002400088,0.0005935188,0.0001132014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001223993,0.00009059403,0.8537984,0.0002702838,0.000106049,0.0001623335,0.001064138,0.0002992623,0.0006942655,0.0004295192,0.1035342,0.03942856],"study_design_scores_gemma":[0.000007040775,0.00002976549,0.9788513,0.00004785531,0.00001793847,0.0001381813,0.0009333428,0.0001161388,0.0001506766,0.00002911096,0.01967184,0.000006735213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.4026538,0.002123331,0.0004245812,0.0003319229,0.0001665868,0.0003576502,0.5549963,0.000263804,0.03868198],"genre_scores_gemma":[0.5776681,0.006137149,0.001326022,0.0004026215,0.00008175681,0.0005094656,0.3582201,0.0001022239,0.05555254],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5537206,"threshold_uncertainty_score":0.8978153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06115968337066998,"score_gpt":0.3293765469181156,"score_spread":0.2682168635474457,"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."}}