{"id":"W2152174952","doi":"10.1093/jeea/jvy027","title":"Missing Unmarried Women","year":2018,"lang":"en","type":"article","venue":"Journal of the European Economic Association","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"","keywords":"Demography; Context (archaeology); China; Missing data; Developing country; Geography; Economics; Sociology; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001516604,0.0001426186,0.0002935706,0.0008525508,0.0006245804,0.0004980668,0.0004635431,0.0003025624,0.01160107],"category_scores_gemma":[0.01036059,0.0001407636,0.0003117765,0.0008364071,0.000258775,0.0007448724,0.0007655509,0.0005049743,0.001422463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001958139,"about_ca_system_score_gemma":0.000433284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004408223,"about_ca_topic_score_gemma":0.005736969,"domain_scores_codex":[0.9989243,0.0003463473,0.0001163752,0.000156257,0.0002388182,0.0002178902],"domain_scores_gemma":[0.9942188,0.001677358,0.002501738,0.0006151356,0.0005750709,0.0004118491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002264065,0.00008071709,0.8527573,0.0003601174,0.0001046823,0.0004018813,0.002637025,0.0003034384,0.000528513,0.004411535,0.01308984,0.1250986],"study_design_scores_gemma":[0.00002843477,0.0003451318,0.937163,0.000605621,0.0001251728,0.002470778,0.008226064,0.001444588,0.001496319,0.00567737,0.04238098,0.00003643555],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9581185,0.002708974,0.002979766,0.00243359,0.0001902814,0.00006758172,0.01478193,0.00004885578,0.01867054],"genre_scores_gemma":[0.9903771,0.001304765,0.0007876603,0.000829774,0.00007154606,0.00005384011,0.002603513,0.000006684091,0.003965121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01160107,"threshold_uncertainty_score":0.03880942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02017365730023914,"score_gpt":0.2647439972842993,"score_spread":0.2445703399840602,"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."}}