{"id":"W7037729294","doi":"","title":"The Effect of Taking a Paternity Leave on Men’s Career Outcomes","year":2020,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Parental leave; Perception; Agency (philosophy); Expectancy theory; Test (biology); Sample (material)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005433354,0.0002654365,0.0004330777,0.000508527,0.002099815,0.00149813,0.0007848383,0.000698933,0.0114792],"category_scores_gemma":[0.02526335,0.0001879413,0.0008318056,0.0005454242,0.001132254,0.0007734649,0.001607704,0.002200092,0.0006261563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001281799,"about_ca_system_score_gemma":0.00252553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02590763,"about_ca_topic_score_gemma":0.03860362,"domain_scores_codex":[0.9964497,0.001678155,0.0001478659,0.000420686,0.0005658973,0.0007376477],"domain_scores_gemma":[0.9752173,0.01017788,0.006850414,0.001626142,0.0009451894,0.005183016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001437465,0.001300607,0.9560395,0.00008471396,0.0002998805,0.00008851401,0.002627748,0.0003893614,0.000266599,0.001744896,0.001062806,0.03465795],"study_design_scores_gemma":[0.00005121039,0.0007952608,0.9937322,0.00005720673,0.0001018018,0.00002561327,0.00276546,0.0005076973,0.00021141,0.0006940918,0.00103967,0.00001848616],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995245,0.0003608767,0.0002492699,0.00117762,0.00005372452,0.00002195494,0.0002204685,0.000009948856,0.002661174],"genre_scores_gemma":[0.9982868,0.0001264912,0.0001468769,0.00008615425,0.00002308665,0.00002052897,0.0001178555,0.000003737943,0.001188359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02590763,"threshold_uncertainty_score":0.05151367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06627739889284377,"score_gpt":0.357201921387949,"score_spread":0.2909245224951052,"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."}}