{"id":"W4233356408","doi":"10.4095/301524","title":"Sex Composition (female) by Marital Status, 2006 - Married (by census subdivision)","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":"Subdivision; Census; Marital status; Geography; Composition (language); Demography; Sociology; Population; Archaeology; 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":[0.0002373792,0.0002716315,0.0002160829,0.001968759,0.0006006096,0.0005008216,0.0005780234,0.0001515317,0.009101666],"category_scores_gemma":[0.001126401,0.0001727985,0.0003219628,0.002740306,0.0001256126,0.0003229004,0.0004087887,0.0002729677,0.003503072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136466,"about_ca_system_score_gemma":0.00154048,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5351521,"about_ca_topic_score_gemma":0.6680958,"domain_scores_codex":[0.9996611,0.00002173476,0.00003722189,0.00004708627,0.0001559571,0.0000769068],"domain_scores_gemma":[0.9993678,0.00002182839,0.0001402806,0.00002392713,0.000343875,0.0001023458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001304122,0.0000802088,0.9065874,0.000162008,0.00009569115,0.0001622692,0.001037339,0.0002774503,0.0007604797,0.0003638492,0.05982858,0.03051426],"study_design_scores_gemma":[0.000006036642,0.0000222691,0.9849204,0.00002848158,0.00001022689,0.0001166376,0.0007250634,0.000103834,0.0000912684,0.00002449849,0.01394633,0.000004945842],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5742065,0.002386612,0.0005003083,0.0003401037,0.0001273651,0.0003652045,0.3731376,0.0001698712,0.04876632],"genre_scores_gemma":[0.7518738,0.005099323,0.001058063,0.0003628956,0.00006710077,0.0002869388,0.1831919,0.0000782647,0.05798169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5351521,"threshold_uncertainty_score":0.9351709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03804933255815506,"score_gpt":0.3317477644606997,"score_spread":0.2936984319025446,"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."}}