{"id":"W4238992828","doi":"10.4095/301495","title":"Sex Composition (male) by Age, 2006 - Golden Years by Census Division (65 - 79 years old)","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; Demography; Composition (language); Division (mathematics); Geography; Genealogy; History; Sociology; Art; Mathematics; Population; Arithmetic; Literature","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":[0.000252237,0.0004500607,0.0002691846,0.002763619,0.0006002422,0.0004876002,0.0006757411,0.0001807466,0.01001441],"category_scores_gemma":[0.001154922,0.0002012707,0.0004231197,0.003787798,0.0001213442,0.0003859632,0.0004054313,0.0003814504,0.005177676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001532807,"about_ca_system_score_gemma":0.002540663,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6019199,"about_ca_topic_score_gemma":0.7279003,"domain_scores_codex":[0.9995473,0.00002085804,0.00004383349,0.00005228197,0.0002275823,0.0001080727],"domain_scores_gemma":[0.9991055,0.00002288988,0.0001469877,0.00002214825,0.0005991003,0.0001034219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001717427,0.0001093917,0.7029123,0.0004508578,0.0001486201,0.0002076256,0.0008482456,0.0003921037,0.0008519034,0.0005604227,0.2410084,0.0523383],"study_design_scores_gemma":[0.00001390013,0.00003321691,0.9596867,0.00008502756,0.00002339059,0.0001837151,0.0008646598,0.0001340148,0.0001528451,0.00004651326,0.03876668,0.000009334617],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2254016,0.002670001,0.0004474042,0.0003759675,0.0002543421,0.0004367305,0.7158871,0.0002510061,0.05427575],"genre_scores_gemma":[0.452048,0.008288582,0.001371926,0.0006209501,0.0001228631,0.0007027421,0.4588039,0.00009992071,0.07794105],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3980801,"threshold_uncertainty_score":0.8008488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03839038419650797,"score_gpt":0.3274683236163261,"score_spread":0.2890779394198181,"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."}}