{"id":"W2085249160","doi":"10.1002/sim.3448","title":"Statistical issues in the design and analysis of expertise‐based randomized clinical trials","year":2008,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Hip disorders and treatments","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canadian Institutes of Health Research","keywords":"Randomized controlled trial; Research design; Confounding; Medicine; Clinical study design; Medical physics; Intervention (counseling); Completely randomized design; Computer science; Randomized experiment; Clinical trial; Physical therapy; Statistics; Surgery; Mathematics; Nursing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0112017,0.0001532486,0.002501603,0.0004074737,0.00003157913,0.000002815376,0.00007017681,0.00008124916,0.0003238473],"category_scores_gemma":[0.02443175,0.00008022321,0.00009203691,0.0005763961,0.001036557,0.00001321144,0.000009285702,0.0001981821,0.000001649755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002213538,"about_ca_system_score_gemma":0.00009969949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005622379,"about_ca_topic_score_gemma":0.00008151278,"domain_scores_codex":[0.9938619,0.003652664,0.001609716,0.000244069,0.0004530073,0.0001786834],"domain_scores_gemma":[0.976397,0.02295591,0.0002313738,0.0002479203,0.0000757207,0.00009206367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"randomized_trial","study_design_scores_codex":[0.1378921,0.004190587,0.7187226,0.0002949485,0.005145303,0.004917753,0.0202,0.0002860804,0.00007247384,0.02263867,0.02617675,0.05946277],"study_design_scores_gemma":[0.4195578,0.001867563,0.4117742,0.0003005903,0.008205886,0.00002366877,0.001198041,0.1498407,0.00002144041,0.006761978,0.000230376,0.0002178207],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06593174,0.003225866,0.9257994,0.002525625,0.0001018674,0.001912555,0.0001416522,0.00001065574,0.0003506033],"genre_scores_gemma":[0.9174888,0.002887702,0.07850777,0.0007052438,0.00004443458,0.00007893395,0.0002209244,0.0000109077,0.00005524329],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8515571,"threshold_uncertainty_score":0.9837859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1771878497156139,"score_gpt":0.5005786867762901,"score_spread":0.3233908370606763,"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."}}