{"id":"W2547935594","doi":"","title":"The Subcluster Wild Bootstrap for Few (Treated) Clusters","year":2016,"lang":"en","type":"preprint","venue":"Carleton University's Institutional Repository (MacOdrum Library, Carleton University)","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Queen's University","keywords":"Cluster (spacecraft); Inference; Econometrics; Statistics; Computer science; Mathematics; Artificial intelligence","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0003629987,0.0009610766,0.0009577343,0.0007230443,0.002826269,0.0003893115,0.002405592,0.001038363,0.000095626],"category_scores_gemma":[0.0003402487,0.0008419495,0.001001621,0.0005682472,0.001844156,0.0009679648,0.002191495,0.001137274,0.00001909385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001408988,"about_ca_system_score_gemma":0.002252597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001048416,"about_ca_topic_score_gemma":0.00002884489,"domain_scores_codex":[0.9952058,0.0007546786,0.0006718677,0.001531617,0.0008100642,0.001026009],"domain_scores_gemma":[0.9935815,0.003144508,0.0007734183,0.001363042,0.0004821094,0.0006554319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001414057,0.0001583584,0.001054444,0.0005300133,0.000801634,0.001331246,0.000173426,0.0001645562,0.0005270886,0.9519772,0.03967297,0.002194989],"study_design_scores_gemma":[0.003390841,0.0002979132,0.0007312878,0.001223583,0.001234273,0.0001151218,0.001141273,0.0006935105,0.002781373,0.04904966,0.9374445,0.001896679],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0553426,0.0007005747,0.2537498,0.005615308,0.009703918,0.004608977,0.004028512,0.001600819,0.6646495],"genre_scores_gemma":[0.4670209,0.001935821,0.05505708,0.001116807,0.003555266,0.00002829616,0.0007184742,0.0004696281,0.4700978],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9029276,"threshold_uncertainty_score":0.9994031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04417783807424663,"score_gpt":0.2661698602942464,"score_spread":0.2219920222199998,"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."}}