{"id":"W4319058127","doi":"10.1002/sim.9663","title":"The Personalised Randomized Controlled Trial: Evaluation of a new trial design","year":2023,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Menzies Centre for Australian Studies, King's College London, University of London; Medical Research Council Canada; King's College London; Medical Research Council; National Institute for Health and Care Research","keywords":"Randomized controlled trial; Pooling; Randomization; Computer science; Clinical trial; Ranking (information retrieval); Outcome (game theory); Medicine; Intervention (counseling); Machine learning; Artificial intelligence; Mathematics; Surgery; Psychiatry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02797174,0.0001619953,0.001420439,0.0001820295,0.00005813149,0.000008561518,0.0001966222,0.00007405569,0.0002036413],"category_scores_gemma":[0.1393912,0.00008930849,0.00008321807,0.000391539,0.0003461859,0.00003155602,0.00002406865,0.000184206,0.000004466012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008924279,"about_ca_system_score_gemma":0.0003731539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004881516,"about_ca_topic_score_gemma":0.00003307938,"domain_scores_codex":[0.9947929,0.002130575,0.001351075,0.0001784985,0.00130981,0.0002371535],"domain_scores_gemma":[0.9621731,0.03644032,0.0006090598,0.0003017912,0.0004207036,0.0000550115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","study_design_scores_codex":[0.807366,0.00003005616,1.407016e-7,0.00001349688,0.00006963203,0.000002716193,0.000955619,0.00002671525,0.00007341924,0.1695362,0.01845885,0.003467218],"study_design_scores_gemma":[0.5040283,0.0003758227,4.251453e-7,0.00006271382,0.000247467,2.173448e-7,0.0002211474,0.01555191,0.00003877407,0.4794095,0.00002113972,0.000042604],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006143678,0.0002716038,0.9702922,0.00113549,0.000899039,0.01956346,0.00001592612,0.0001798534,0.001498751],"genre_scores_gemma":[0.2978032,0.002916623,0.6740593,0.0002879673,0.002367116,0.01395121,0.0001650291,0.0002147848,0.008234729],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3098733,"threshold_uncertainty_score":0.9694501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3224457499803688,"score_gpt":0.5144343715594577,"score_spread":0.1919886215790889,"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."}}