{"id":"W2124547615","doi":"10.1136/bmj.e5278","title":"Sample size calculations: should the emperor's clothes be off the peg or made to measure?","year":2012,"lang":"en","type":"article","venue":"BMJ","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":189,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hamilton Health Sciences; McMaster University","funders":"","keywords":"Emperor; Measure (data warehouse); Clothing; Sample size determination; Sample (material); Statistics; Econometrics; Psychology; Computer science; Mathematics; History; Data mining; Archaeology; Physics; Thermodynamics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.1074328,0.0002102486,0.001192868,0.00007478565,0.0004141943,0.0006752457,0.001908811,0.00006333575,0.01769531],"category_scores_gemma":[0.1783031,0.00005739287,0.000974746,0.001170553,0.0000662042,0.0001873131,0.0001635854,0.0001268229,0.004201116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002362793,"about_ca_system_score_gemma":0.0000645105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008194338,"about_ca_topic_score_gemma":0.0002598131,"domain_scores_codex":[0.9844556,0.006591749,0.003665839,0.0004164287,0.004540224,0.0003302005],"domain_scores_gemma":[0.9600073,0.03211293,0.001665834,0.005343743,0.0006402186,0.0002299928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001199551,0.00004403231,0.0207608,0.000008010861,0.0001853626,5.468066e-7,0.003698431,0.0001123461,0.00009539004,0.00512098,0.9450349,0.02492719],"study_design_scores_gemma":[0.00005551978,0.00001159431,0.06715105,0.00001215675,0.0001694546,0.00001080979,0.001869625,0.0005676415,0.00002238342,0.001547772,0.9284719,0.0001101515],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2535849,0.010837,0.09089331,0.5674204,0.003407679,0.01339063,0.0002205382,0.00007022479,0.06017535],"genre_scores_gemma":[0.9345772,0.00001636431,0.01049986,0.010337,0.0008501253,0.0003548322,0.000001625659,0.00002043566,0.04334253],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6809923,"threshold_uncertainty_score":0.9965742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8549429062449583,"score_gpt":0.5627533083106878,"score_spread":0.2921895979342705,"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."}}