{"id":"W2106094950","doi":"10.1177/1740774512467404","title":"Determining optimal sample sizes for multistage adaptive randomized clinical trials from an industry perspective using value of information methods","year":2012,"lang":"en","type":"article","venue":"Clinical Trials","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Frequentist inference; Sample size determination; Profit (economics); Value of information; Randomized controlled trial; Bayesian probability; Expected utility hypothesis; Computer science; Actuarial science; Econometrics; Statistics; Medicine; Economics; Mathematics; Bayesian inference; Microeconomics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05812281,0.001358014,0.002351743,0.002878649,0.0005387017,0.001906609,0.002146053,0.002862531,0.003199481],"category_scores_gemma":[0.1089948,0.001164352,0.001842211,0.001720368,0.002071715,0.002585597,0.00234974,0.003876407,0.0004032739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003239489,"about_ca_system_score_gemma":0.005000934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001077097,"about_ca_topic_score_gemma":0.001349522,"domain_scores_codex":[0.9340034,0.05809418,0.001260333,0.002074752,0.00387844,0.0006890202],"domain_scores_gemma":[0.8442204,0.1457958,0.004723542,0.001887288,0.002695025,0.0006779009],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001753651,0.0007121082,0.005617377,0.00155481,0.0004884065,0.0003238009,0.0006061977,0.5270572,0.002880987,0.2629009,0.002680478,0.193424],"study_design_scores_gemma":[0.0008696971,0.001087437,0.001215602,0.000383054,0.0001469533,0.0001246974,0.0001025022,0.7858241,0.001978578,0.2050569,0.003141145,0.00006942885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006660657,0.0004154544,0.9900595,0.0005929989,0.00003055604,0.001003968,0.00004651311,0.000062097,0.001128279],"genre_scores_gemma":[0.180597,0.0005610111,0.8141321,0.0003411137,0.00007041627,0.003580765,0.00009720532,0.00004438266,0.0005758856],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9418772,"threshold_uncertainty_score":0.3073864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.901972840808825,"score_gpt":0.7468425831810588,"score_spread":0.1551302576277662,"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."}}