{"id":"W2013102726","doi":"10.1038/bjc.2011.157","title":"Statistical issues in the use of dynamic allocation methods for balancing baseline covariates","year":2011,"lang":"en","type":"article","venue":"British Journal of Cancer","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Juravinski Hospital; Ontario Clinical Oncology Group; McMaster University","funders":"","keywords":"Clinical trial; Credibility; Statistical inference; Baseline (sea); Covariate; Inference; Computer science; Medicine; Statistics; Artificial intelligence; Machine learning; Mathematics","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"],"consensus_categories":[],"category_scores_codex":[0.01052219,0.00009568878,0.0005924929,0.00005899237,0.00003136436,0.00003839318,0.0002498564,0.00008768996,0.0003131428],"category_scores_gemma":[0.1213578,0.00007750255,0.0001131039,0.000140715,0.0001176015,0.0001212551,0.00002170469,0.0002674654,3.355482e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005061506,"about_ca_system_score_gemma":0.0001056773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003871174,"about_ca_topic_score_gemma":0.0002770662,"domain_scores_codex":[0.9962061,0.001837673,0.001386737,0.0001276849,0.0002631206,0.0001786684],"domain_scores_gemma":[0.9477099,0.05093898,0.0006761951,0.0001402096,0.0004807161,0.00005403398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004547048,0.0003410711,0.0004022442,0.0002567653,0.0001386806,0.00004431235,0.0005502615,0.00001791362,0.0004507041,0.04370369,0.003112998,0.9505267],"study_design_scores_gemma":[0.00134453,0.0002568439,0.01019105,0.0007964098,0.0002756754,0.0001059816,0.0001047663,0.006987011,0.000748886,0.9768525,0.002204271,0.0001320777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003618156,0.001178219,0.9939712,0.0002660448,0.000431946,0.0003134317,0.0001879877,0.000005074511,0.00002791545],"genre_scores_gemma":[0.01078251,0.001004394,0.9877765,0.0001924953,0.0001590902,0.0000275015,0.000001201081,0.00002067846,0.00003563392],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9503946,"threshold_uncertainty_score":0.8860434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5326053452684013,"score_gpt":0.5987837027161158,"score_spread":0.0661783574477145,"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."}}