{"id":"W4236737173","doi":"10.4095/301501","title":"Sex Composition (female) by Age, 2006 - Golden Years by Census Subdivision (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; Subdivision; Demography; Composition (language); Geography; Genealogy; History; Art; Sociology; Archaeology; Population; 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":[0.00025661,0.0004011538,0.0002485344,0.002463849,0.0005588063,0.0004625141,0.0006530203,0.0001768481,0.008902561],"category_scores_gemma":[0.00112792,0.0001728301,0.0003984093,0.003142489,0.000123542,0.000337875,0.0004165586,0.0003369168,0.004296145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001492902,"about_ca_system_score_gemma":0.002320327,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6256807,"about_ca_topic_score_gemma":0.7506972,"domain_scores_codex":[0.9996008,0.00002180468,0.00003755702,0.0000504445,0.0001892081,0.0001001185],"domain_scores_gemma":[0.9991729,0.00002168761,0.0001287622,0.00002285881,0.0005551081,0.00009869303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001454912,0.00007895913,0.8196449,0.0002493326,0.0001077485,0.0001886829,0.0008988833,0.0003473567,0.0008763839,0.0004654907,0.1378136,0.03918314],"study_design_scores_gemma":[0.0000091371,0.00002536513,0.9737648,0.00005240272,0.00001603683,0.0001594859,0.0008578827,0.0001205756,0.0001428315,0.00003712342,0.02480727,0.000007176376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3567592,0.002103678,0.0004893943,0.0003940433,0.0001796733,0.0004028448,0.5864643,0.0002376293,0.05296926],"genre_scores_gemma":[0.5603599,0.005215243,0.001268021,0.0004606107,0.00007879283,0.0004926628,0.3581609,0.0000910722,0.07387278],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6256807,"threshold_uncertainty_score":0.7530475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04385366401517541,"score_gpt":0.3338704891428845,"score_spread":0.2900168251277091,"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."}}