{"id":"W2020516125","doi":"10.15185/izawol.77","title":"Human capital effects of marriage payments","year":2014,"lang":"en","type":"article","venue":"IZA World of Labor","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Payment; Human capital; Economics; Business; Labour economics; Monetary economics; Finance; Market economy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003348927,0.00007297048,0.0001802228,0.0001285164,0.0001155961,0.00001459177,0.0002409919,0.00003674076,0.000220982],"category_scores_gemma":[0.00006707979,0.00006301249,0.00006307045,0.0004229702,0.0002292661,0.00007311466,0.00003234851,0.00005329604,0.000006180816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006139674,"about_ca_system_score_gemma":0.00002701991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001256757,"about_ca_topic_score_gemma":0.01049861,"domain_scores_codex":[0.9990438,0.0001622179,0.0001800133,0.0001335462,0.000296534,0.0001839083],"domain_scores_gemma":[0.9994658,0.000123853,0.0001265142,0.0001510852,0.0000606861,0.00007204246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001237865,0.0003132264,0.3703917,0.000215578,0.0001173686,0.000003483124,0.0224715,0.000001782428,0.003709766,0.5627508,0.003584729,0.03642773],"study_design_scores_gemma":[0.0008899408,0.0002070044,0.9007786,0.0001421845,0.00005853003,8.10838e-8,0.001280169,0.000001796935,0.006559428,0.04876408,0.0410741,0.0002441084],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9421543,0.0002067518,0.00001097267,0.0003019122,0.0003326263,0.00009959756,0.00001018519,0.00002784065,0.05685583],"genre_scores_gemma":[0.995564,0.00001720395,0.0001458604,0.0000536483,0.00009574781,0.000005704196,0.000002203308,0.000005330428,0.004110265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5303869,"threshold_uncertainty_score":0.5858469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01294763456250664,"score_gpt":0.2914531823360352,"score_spread":0.2785055477735285,"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."}}