{"id":"W4250657258","doi":"10.4095/301496","title":"Sex Composition (male) by Age, 2006 - Later Working Years by Census Division (35 - 64 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; Composition (language); Division (mathematics); Demography; Geography; Genealogy; History; Sociology; Art; Arithmetic; Mathematics; Population","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":[0.0002742067,0.0004066688,0.000242835,0.002658624,0.0006027941,0.0005110404,0.0007345456,0.0001800541,0.01002339],"category_scores_gemma":[0.001131568,0.0002029823,0.0004108865,0.003166895,0.0001200533,0.0003884374,0.0003709398,0.0003506468,0.004864556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001276475,"about_ca_system_score_gemma":0.00199269,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5368237,"about_ca_topic_score_gemma":0.6739329,"domain_scores_codex":[0.9995832,0.00002101155,0.00004322636,0.00005412702,0.0001996559,0.00009866344],"domain_scores_gemma":[0.999119,0.00002809257,0.0001612773,0.00002811076,0.0005530132,0.0001105779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001275246,0.0001023084,0.8130826,0.0002996087,0.000117681,0.000175569,0.0009820015,0.0003334299,0.000859993,0.000425394,0.1385867,0.04490715],"study_design_scores_gemma":[0.00000984904,0.00002965138,0.9705584,0.00006324457,0.00001748149,0.0001616455,0.0009300678,0.0001172208,0.0001472736,0.0000333047,0.02792285,0.000009048431],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3475057,0.002626576,0.0005120376,0.0003640653,0.000222314,0.0004628319,0.5953536,0.0002471687,0.05270557],"genre_scores_gemma":[0.5801095,0.007629476,0.001493654,0.0005678015,0.0001071202,0.0007276473,0.3302762,0.0001018887,0.0789867],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5368237,"threshold_uncertainty_score":0.931808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0468949220061873,"score_gpt":0.3223768933349422,"score_spread":0.2754819713287549,"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."}}