{"id":"W7164926533","doi":"10.1080/17153379.2024.12558429","title":"Marriage Unbound: State Law, Power, and Inequality in Contemporary China.","year":2024,"lang":"en","type":"article","venue":"Pacific Affairs","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Inequality; State (computer science)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0005687168,0.00007967377,0.0001245816,0.0009695902,0.002455072,0.001127133,0.0003356524,0.0003121849,0.005474823],"category_scores_gemma":[0.001129281,0.00006839977,0.00009278123,0.001468819,0.002213974,0.001304474,0.001119988,0.0006820988,0.0001332494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165399,"about_ca_system_score_gemma":0.002127666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06998844,"about_ca_topic_score_gemma":0.2247694,"domain_scores_codex":[0.9997229,0.00005816467,0.00001197478,0.00003127502,0.00004311065,0.0001325537],"domain_scores_gemma":[0.9995226,0.00008664536,0.0001297836,0.00002248296,0.00006100601,0.0001775641],"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":[0.00009150544,0.0001342192,0.7905012,0.00005673689,0.00003508162,0.0003515599,0.04846174,0.0003603732,0.0004402158,0.09669495,0.002978858,0.05989354],"study_design_scores_gemma":[0.000004897855,0.00004621406,0.9508293,0.00005050755,0.00001630899,0.00005753995,0.02834341,0.0007949485,0.0001073762,0.01073181,0.009005344,0.00001237051],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9855627,0.0007122383,0.0001018752,0.002256215,0.00001278876,0.000004197239,0.00008518683,0.000002461533,0.01126229],"genre_scores_gemma":[0.9988205,0.0001908861,0.00001200039,0.00006674798,0.000008334618,0.000001975813,0.00001966415,5.793062e-7,0.0008793136],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.06998844,"threshold_uncertainty_score":0.1391621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0381942558768192,"score_gpt":0.3075224579569117,"score_spread":0.2693282020800926,"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."}}