{"id":"W4294233607","doi":"10.15626/mp.2021.2720","title":"Z-curve 2.0: Estimating Replication Rates and Discovery Rates","year":2022,"lang":"en","type":"article","venue":"Meta-Psychology","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Replication (statistics); Confidence interval; False discovery rate; Statistics; Selection (genetic algorithm); False positive paradox; Multiple comparisons problem; Computer science; Range (aeronautics); Extension (predicate logic); Statistical power; Econometrics; Mathematics; Artificial intelligence; Biology; Engineering","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.342165,0.005295318,0.00670114,0.01417589,0.002363022,0.008945033,0.007793545,0.00563793,0.03242816],"category_scores_gemma":[0.7177069,0.00570673,0.01524841,0.01680871,0.005180774,0.007370513,0.009409021,0.00908967,0.01099639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003022735,"about_ca_system_score_gemma":0.01062014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004232168,"about_ca_topic_score_gemma":0.003477157,"domain_scores_codex":[0.680928,0.2535161,0.02220012,0.02070647,0.02071514,0.001934108],"domain_scores_gemma":[0.3353841,0.5348835,0.02833064,0.0709689,0.02885255,0.001580347],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00703854,0.0004350613,0.05436391,0.02564268,0.03273343,0.001105923,0.007051914,0.04063437,0.004889577,0.1404307,0.1420029,0.543671],"study_design_scores_gemma":[0.006353006,0.001834143,0.03767527,0.007169317,0.01611611,0.002059476,0.0009045934,0.1776503,0.01587936,0.3640226,0.3688277,0.001508115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004777447,0.00292781,0.9509302,0.001631557,0.001133932,0.008203363,0.01141744,0.01414178,0.004836496],"genre_scores_gemma":[0.0426843,0.001207307,0.9013984,0.0008049562,0.0003008787,0.03849696,0.004752269,0.008236422,0.002118522],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.657835,"threshold_uncertainty_score":0.8112277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7276317683307449,"score_gpt":0.64387429511749,"score_spread":0.083757473213255,"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."}}