{"id":"W2561787847","doi":"10.3386/w22950","title":"Targeting Policies: Multiple Testing and Distributional Treatment Eﬀects","year":2016,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Michigan Diabetes Research Center, University of Michigan","keywords":"Computer science; Economics; Econometrics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004640253,0.000188871,0.0003583031,0.000369746,0.0007362416,0.00009770528,0.0002935464,0.0003525405,0.0001306434],"category_scores_gemma":[0.009229513,0.0001661359,0.00009496266,0.0001934815,0.0007271546,0.0001409185,0.0001227477,0.0002626678,0.00004333982],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004937836,"about_ca_system_score_gemma":0.009853061,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02693724,"about_ca_topic_score_gemma":0.001752348,"domain_scores_codex":[0.9967206,0.0002526872,0.0005023903,0.0004583008,0.00148152,0.0005844611],"domain_scores_gemma":[0.9925131,0.004491218,0.0002756857,0.0001399085,0.002394575,0.0001855542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005285437,0.0003090166,0.4203742,0.0002237999,0.0005151,0.000009669987,0.003676964,0.0003683228,0.0006162997,0.5293632,0.03791506,0.006575537],"study_design_scores_gemma":[0.003176634,0.0005686934,0.1176388,0.0006728245,0.00008241002,0.00002629097,0.009306109,0.003610871,0.00008417201,0.5633763,0.2998838,0.001573047],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08034566,0.00161683,0.00004517758,0.001525498,0.00100461,0.001105465,0.002156461,0.00005703851,0.9121433],"genre_scores_gemma":[0.9831728,0.003985518,0.0003637182,0.000009795818,0.002329153,0.00007734959,0.0004392518,0.00002661228,0.009595846],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9028271,"threshold_uncertainty_score":0.9991162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3520851917905788,"score_gpt":0.5063554751075703,"score_spread":0.1542702833169914,"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."}}