{"id":"W2142603336","doi":"10.1002/cjs.5550360403","title":"Bootstrapping data with multiple levels of variation","year":2008,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Bootstrapping (finance); Estimator; Variation (astronomy); Statistics; Variance (accounting); Transformation (genetics); Mathematics; Random effects model; Gaussian; Applied mathematics; Econometrics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004005528,0.00008981408,0.0002682743,0.0001198377,0.0000865429,0.00001421199,0.0002923594,0.00004054887,0.0002117353],"category_scores_gemma":[0.005212692,0.00007338382,0.00001497702,0.0001226921,0.0001615032,0.00009934794,0.00001179812,0.0001651037,0.000001448093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004452563,"about_ca_system_score_gemma":0.001342243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001198545,"about_ca_topic_score_gemma":0.004218844,"domain_scores_codex":[0.9989553,0.00006799633,0.0004842302,0.00009311237,0.0002167625,0.000182565],"domain_scores_gemma":[0.9971449,0.001382348,0.0004203359,0.0002713921,0.0004689243,0.0003120875],"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":[0.0001337133,0.0001569563,0.04369454,0.0005744344,0.0005432399,0.002245177,0.005996568,0.0002612215,0.0009876873,0.869822,0.03491234,0.04067216],"study_design_scores_gemma":[0.003375628,0.001205172,0.4597529,0.0007569918,0.0004300363,0.001711028,0.0005536744,0.02596896,0.0006702362,0.5010943,0.003788824,0.0006921837],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01694995,0.00003782369,0.9796048,0.00004214972,0.0001181131,0.00005939003,0.002804614,0.000002305497,0.0003808144],"genre_scores_gemma":[0.497484,0.000005955897,0.5024205,0.00001814218,0.00003761377,1.851018e-7,0.000004590727,0.0000082935,0.00002076823],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.480534,"threshold_uncertainty_score":0.6240455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2894951086117069,"score_gpt":0.3461501369616866,"score_spread":0.05665502834997965,"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."}}