{"id":"W4232474794","doi":"10.4095/301518","title":"Sex Composition (female) by Marital Status, 2006 - Widowed (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; Marital status; Subdivision; Demography; Composition (language); Geography; Gerontology; Sociology; Medicine; Archaeology; Art; 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":[0.0002213277,0.0002633769,0.000201176,0.001679439,0.0005525806,0.0004686469,0.0005477367,0.0001527201,0.00874562],"category_scores_gemma":[0.0009559495,0.0001738124,0.0003199205,0.002209788,0.0001231142,0.0003230688,0.0004245605,0.0002674683,0.00316923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008132663,"about_ca_system_score_gemma":0.001139165,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3997011,"about_ca_topic_score_gemma":0.5580751,"domain_scores_codex":[0.9997292,0.00002082175,0.00003475844,0.00004052342,0.0001041265,0.0000704775],"domain_scores_gemma":[0.9994667,0.00002228904,0.0001378491,0.00002262385,0.0002582637,0.00009218218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001380146,0.00007758119,0.9347975,0.0001286148,0.00009182566,0.0001413557,0.000921477,0.000227419,0.0007659158,0.0002698989,0.03737576,0.02506455],"study_design_scores_gemma":[0.000005873534,0.00002752672,0.9894186,0.00002492003,0.00001123198,0.0001181486,0.0007478675,0.00008456893,0.00009825653,0.00001965037,0.009438297,0.000005024034],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7080752,0.001862554,0.0004099531,0.0002628037,0.00009227855,0.0002792641,0.2565506,0.0001316442,0.03233582],"genre_scores_gemma":[0.8103157,0.004039446,0.0008884658,0.0003063414,0.00005267948,0.0002632068,0.1376566,0.00005829286,0.04641942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6002989,"threshold_uncertainty_score":0.7947492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03686626835048082,"score_gpt":0.3314538615762708,"score_spread":0.29458759322579,"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."}}