{"id":"W4254077213","doi":"10.4095/301510","title":"Sex Composition (male) by Marital Status, 2006 - Separated (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":"Census; Subdivision; Composition (language); Demography; Marital status; Geography; Psychology; Sociology; Art; Archaeology; 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":[0.0002354129,0.0002910435,0.0002343297,0.001957321,0.0006637239,0.0005141674,0.0006765237,0.0001634106,0.008091315],"category_scores_gemma":[0.001107413,0.0001913631,0.0003495402,0.00284774,0.0001367064,0.0003241403,0.000442904,0.0003049887,0.003320602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001298459,"about_ca_system_score_gemma":0.001834807,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5995474,"about_ca_topic_score_gemma":0.7424529,"domain_scores_codex":[0.9996186,0.00002448951,0.00003910246,0.00004773169,0.0001809645,0.00008901361],"domain_scores_gemma":[0.999233,0.00002495898,0.0001641661,0.00002828941,0.0004197514,0.0001298329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001486341,0.0001017499,0.9124845,0.000181785,0.0001298143,0.0001841438,0.001360636,0.0002930196,0.0008644474,0.0004067606,0.0542875,0.02955691],"study_design_scores_gemma":[0.00000625517,0.00002340312,0.9872167,0.00002836426,0.00001091582,0.0001104386,0.0008186306,0.0001107346,0.00008684689,0.000025769,0.01155672,0.000005318717],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.6284601,0.002225593,0.0004475878,0.0003055166,0.0001098536,0.0003031778,0.3288406,0.0001662726,0.03914139],"genre_scores_gemma":[0.7695704,0.004104374,0.0009991643,0.000314178,0.00005665263,0.0002474818,0.1765149,0.00006605971,0.04812672],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.4004526,"threshold_uncertainty_score":0.8056218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03546969127315379,"score_gpt":0.3389012385756786,"score_spread":0.3034315473025248,"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."}}