{"id":"W2020776773","doi":"10.1111/j.0006-341x.2003.00127.x","title":"Issues of Cost and Efficiency in the Design of Reliability Studies","year":2003,"lang":"en","type":"article","venue":"Biometrics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Intraclass correlation; Reliability (semiconductor); Variance (accounting); Statistics; Reliability engineering; Mathematics; Computer science; Psychometrics; Engineering; Economics; Power (physics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.4983711,0.002822377,0.005892395,0.004508917,0.001747421,0.005909027,0.005423444,0.004380032,0.004961743],"category_scores_gemma":[0.7693245,0.002804825,0.002530366,0.006600522,0.009526574,0.00708704,0.005888212,0.007525068,0.001733455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005658102,"about_ca_system_score_gemma":0.008433389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002034694,"about_ca_topic_score_gemma":0.00273443,"domain_scores_codex":[0.3059094,0.6395147,0.02000384,0.005637823,0.02749778,0.001436547],"domain_scores_gemma":[0.09202483,0.85361,0.01288938,0.02537245,0.01495552,0.001147759],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00423559,0.0005877258,0.006619938,0.004566937,0.00152933,0.0007229475,0.004140974,0.03545854,0.002302118,0.4453297,0.01380974,0.4806965],"study_design_scores_gemma":[0.00244393,0.003564585,0.01504361,0.00463152,0.001113033,0.001858192,0.001599531,0.06950344,0.003779116,0.8512144,0.04477927,0.0004694071],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01255197,0.006920497,0.9466081,0.01824815,0.0009030782,0.003854076,0.0003449914,0.0003549446,0.01021419],"genre_scores_gemma":[0.1487936,0.003329903,0.8249967,0.004247541,0.001264928,0.01524098,0.0002031262,0.0004062102,0.001517086],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5016289,"threshold_uncertainty_score":0.6185977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2439836819691648,"score_gpt":0.4538264988293823,"score_spread":0.2098428168602176,"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."}}