{"id":"W4242895532","doi":"10.3368/jhr.50.3.549","title":"Leaving Boys Behind","year":2015,"lang":"en","type":"article","venue":"The Journal of Human Resources","topic":"School Choice and Performance","field":"Social Sciences","cited_by":190,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Distribution (mathematics); Psychology; Mode (computer interface); Demographic economics; Mathematics education; Decomposition; Demography; Developmental psychology; Sociology; Economics; Mathematics; Computer science; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007637219,0.000162789,0.000250387,0.000667847,0.0009031753,0.0008017687,0.0004652563,0.0002878324,0.01033997],"category_scores_gemma":[0.002315224,0.0001504545,0.0003275581,0.0006629188,0.0002373362,0.0006438458,0.0008850292,0.001128632,0.001513742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003417874,"about_ca_system_score_gemma":0.0007029049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01724426,"about_ca_topic_score_gemma":0.02723946,"domain_scores_codex":[0.9992716,0.0001086685,0.00002980078,0.0001719553,0.0001432145,0.0002748446],"domain_scores_gemma":[0.9977059,0.0002573293,0.0009232204,0.000137737,0.0002694954,0.0007063258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001189311,0.00006841782,0.9397966,0.00005687849,0.00004266336,0.0002888396,0.004831242,0.0001643318,0.0005505431,0.002488854,0.007287132,0.04430536],"study_design_scores_gemma":[0.000005148716,0.00009388956,0.9735154,0.00003976369,0.00002523446,0.0002842223,0.005783036,0.0001502605,0.0003998647,0.0005881774,0.01910452,0.00001055881],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9805189,0.0005620443,0.0007087778,0.001099837,0.0001042969,0.00002483136,0.003714841,0.00003746775,0.01322905],"genre_scores_gemma":[0.9860933,0.0003214845,0.0002267373,0.0003163124,0.00003723675,0.00001438877,0.002445055,0.00001137133,0.01053406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01724426,"threshold_uncertainty_score":0.03459066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07535634288568982,"score_gpt":0.3532528757209349,"score_spread":0.2778965328352451,"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."}}