{"id":"W1602806326","doi":"","title":"Bias Reduction and Likelihood Based Almost-Exactly Sized Hypothesis Testing in Predestricted Likelihoodictive Regressions using the R","year":2009,"lang":"en","type":"article","venue":"The Faculty Digital Archive (New York University)","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; National Science Foundation","keywords":"Statistics; Econometrics; Reduction (mathematics); Mathematics; Statistical hypothesis testing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001709851,0.0002385167,0.000274207,0.000170928,0.0004308092,0.00009831694,0.000295063,0.00006007304,0.00000376654],"category_scores_gemma":[0.002837992,0.0001534152,0.0000826888,0.0007786409,0.0002179223,0.0003027981,0.0001061921,0.0003234562,0.000001614368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000953157,"about_ca_system_score_gemma":0.0001619584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008561306,"about_ca_topic_score_gemma":0.00001890194,"domain_scores_codex":[0.9985914,0.000257408,0.0002296382,0.0003471668,0.0002173199,0.0003570371],"domain_scores_gemma":[0.9954149,0.003869281,0.0002024143,0.0002819285,0.00006816322,0.0001632747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003179207,0.001664271,0.001642602,0.0001079674,0.0003701232,0.0002904208,0.01914943,0.007301729,0.02232958,0.07680447,0.00289386,0.8642663],"study_design_scores_gemma":[0.002196092,0.0003986531,0.00539005,0.0004789486,0.0002340946,0.00005839697,0.005576482,0.02784381,0.0005964276,0.955896,0.0008124428,0.0005185663],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2752702,0.00002466049,0.7113626,0.001371043,0.000044162,0.0009991864,0.0005492992,0.0001832414,0.0101956],"genre_scores_gemma":[0.6086662,0.000006644593,0.3906089,0.00007683194,0.00005255524,0.000001179534,0.00001753571,0.00002233384,0.0005478016],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8790916,"threshold_uncertainty_score":0.625609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2232697880479685,"score_gpt":0.3375310352846663,"score_spread":0.1142612472366978,"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."}}