{"id":"W4253623475","doi":"10.4095/301373","title":"Marital Status, 2006: Separated (by census subdivision)","year":2010,"lang":"en","type":"report","venue":"","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subdivision; Census; Marital status; Geography; Demography; Sociology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.006054366,0.000520746,0.0008752478,0.0007212904,0.0002790287,0.0008808927,0.0009761686,0.001089312,0.005821902],"category_scores_gemma":[0.004095963,0.0003641093,0.0004279169,0.001273649,0.0001684281,0.0003060736,0.0002205001,0.001163569,0.001621503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009260515,"about_ca_system_score_gemma":0.001055126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002832407,"about_ca_topic_score_gemma":0.001021632,"domain_scores_codex":[0.9890707,0.0001977281,0.001832633,0.001380482,0.006731786,0.0007866609],"domain_scores_gemma":[0.9930155,0.0009568442,0.0009412853,0.001175353,0.003463802,0.0004472684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001793135,0.00007933018,0.002759641,0.000008482868,0.00003561242,0.00001615248,0.00002550274,0.00002430027,0.0001055445,0.0001443814,0.9360811,0.06070199],"study_design_scores_gemma":[0.0002468917,0.00005885513,0.003363963,0.00002644985,0.00005106172,0.00003375028,0.0001575506,0.004832976,0.00002265378,0.003756502,0.9869326,0.000516739],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04511075,0.002233704,0.003818515,0.0004501904,0.007483437,0.0006079152,0.003943285,0.000487075,0.9358651],"genre_scores_gemma":[0.4117244,0.004878737,0.002699494,0.0003815501,0.0006730364,0.00004972416,0.005126323,0.0001617842,0.5743049],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3666137,"threshold_uncertainty_score":0.9998811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1711311375732913,"score_gpt":0.4358661668785409,"score_spread":0.2647350293052495,"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."}}