{"id":"W4398992134","doi":"10.7910/dvn/rj7vuq/xhzx9s","title":"Judicial_reforms_Map world.do","year":2018,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Replication (statistics); Productivity; Political science; Judicial reform; Law; Economics; Biology; Economic growth","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001101836,0.0005088038,0.001497578,0.0008211555,0.0002900824,0.0004098143,0.001475663,0.000557363,0.06585176],"category_scores_gemma":[0.0003307026,0.0006944562,0.0003903287,0.0003706424,0.0004428285,0.0006171468,0.0005958507,0.0005019557,0.5715463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004818177,"about_ca_system_score_gemma":0.0001128103,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007247346,"about_ca_topic_score_gemma":0.003309488,"domain_scores_codex":[0.9960724,0.00003162348,0.001696249,0.001271026,0.0001029438,0.0008257462],"domain_scores_gemma":[0.9956987,0.0000626194,0.001496567,0.002334954,0.00006679226,0.0003403912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003242474,0.00008197981,0.0001594633,0.000101169,0.0001810732,0.0000260312,0.00002698149,0.000001008429,1.738642e-7,0.0208114,0.9784559,0.0001223792],"study_design_scores_gemma":[0.0005044678,0.0000821381,0.00007574342,0.0001011593,0.00003969087,0.00000674331,0.00001869477,0.00001415139,0.000002319772,0.02148233,0.976837,0.0008355948],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002835418,0.00002889814,0.0000349433,0.00001366338,0.0065353,0.0004636419,0.9319853,0.00007413725,0.06083576],"genre_scores_gemma":[0.0003044652,0.001104136,0.00007502335,0.0008854796,0.004333319,0.00006047617,0.9905844,0.00008226698,0.00257045],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5056945,"threshold_uncertainty_score":0.9995506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02628891340369489,"score_gpt":0.2237886493014662,"score_spread":0.1974997358977713,"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."}}