{"id":"W3122936966","doi":"10.1920/ps.ifs.2024.0794","title":"Wild Bootstrap Inference for Wildly Different Cluster Sizes","year":2013,"lang":"en","type":"preprint","venue":"","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Queen's University","funders":"","keywords":"Cluster (spacecraft); Estimator; Monte Carlo method; Statistics; Variance (accounting); Inference; Econometrics; Mathematics; Computer science; Artificial intelligence; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.04508608,0.0008757506,0.001983765,0.002934624,0.002371479,0.003469496,0.003850508,0.002925463,0.007478312],"category_scores_gemma":[0.2706231,0.0009192068,0.002334882,0.002666863,0.006913761,0.005766706,0.003195484,0.005104105,0.001099519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001526365,"about_ca_system_score_gemma":0.001511925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003800398,"about_ca_topic_score_gemma":0.003713597,"domain_scores_codex":[0.973469,0.01785422,0.0008975934,0.005034176,0.002023461,0.0007214739],"domain_scores_gemma":[0.7714264,0.1706616,0.005445259,0.04383647,0.00736657,0.001263604],"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":[0.000965538,0.0003651171,0.03313546,0.0004189818,0.001053783,0.0006305586,0.001536892,0.1145298,0.002493596,0.6800955,0.01697419,0.1478006],"study_design_scores_gemma":[0.0001615773,0.0001278089,0.006357272,0.000203222,0.0001292771,0.0002683934,0.0003520604,0.4248373,0.002776074,0.5589355,0.005780824,0.0000706903],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04183862,0.0003434269,0.9541007,0.0004719871,0.0001831572,0.0001641375,0.000348777,0.0005188189,0.002030279],"genre_scores_gemma":[0.6216694,0.0002763305,0.3714658,0.0008084715,0.0002315975,0.0007505935,0.001880483,0.0006012042,0.002316133],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04508608,"threshold_uncertainty_score":0.2384409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07980484684633961,"score_gpt":0.2673825672173066,"score_spread":0.187577720370967,"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."}}