{"id":"W118247452","doi":"10.2139/ssrn.2533736","title":"Marriage Gains: Who Should You Marry ?","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Download; Computer science; World Wide Web; Internet privacy","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":[0.002778293,0.0001337175,0.0003613773,0.0004761293,0.002598235,0.002800739,0.000450756,0.001984324,0.01968219],"category_scores_gemma":[0.0147908,0.0001493286,0.0001526565,0.0004249586,0.002411035,0.003844771,0.001130518,0.003737143,0.002416456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000746667,"about_ca_system_score_gemma":0.001497152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004255011,"about_ca_topic_score_gemma":0.01123623,"domain_scores_codex":[0.999052,0.0004526603,0.00002684888,0.0000617683,0.0001276732,0.0002791548],"domain_scores_gemma":[0.9968154,0.0008926021,0.0005298614,0.00008511003,0.0003963382,0.001280807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009606878,0.001059103,0.2604755,0.0002457541,0.0000995805,0.001324338,0.0570727,0.0002331969,0.0008697328,0.1096443,0.1745334,0.3934816],"study_design_scores_gemma":[0.0001250272,0.0006136567,0.2230785,0.001183093,0.0001131857,0.00203908,0.420697,0.001142883,0.0007213273,0.1427033,0.2074297,0.0001533231],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5185601,0.009860883,0.000888108,0.392448,0.002504156,0.00005696081,0.0004082559,0.00003264116,0.07524087],"genre_scores_gemma":[0.972667,0.003111572,0.0001948491,0.007524194,0.0009220013,0.00001951996,0.0000528746,0.00001809529,0.01548994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01968219,"threshold_uncertainty_score":0.06584352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02009264321003311,"score_gpt":0.2879971586820813,"score_spread":0.2679045154720481,"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."}}