{"id":"W3193121389","doi":"10.1371/journal.pone.0253425","title":"Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study","year":2021,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Seventh Framework Programme; ZNS - Hannelore Kohl Stiftung; Bill and Melinda Gates Foundation; European Commission; One Mind; University of Manitoba; Integra LifeSciences","keywords":"Missing data; Covariate; Imputation (statistics); Logistic regression; Glasgow Coma Scale; Statistics; Time point; Traumatic brain injury; Medicine; Pooling; Computer science; Artificial intelligence; Mathematics; Surgery; Psychiatry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1132222,0.001029349,0.002193147,0.00129495,0.0008650231,0.0016084,0.005097859,0.001450178,0.004172806],"category_scores_gemma":[0.2044597,0.0007456523,0.004143777,0.004100071,0.0005271299,0.001060436,0.002326196,0.002351055,0.0007335407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007409786,"about_ca_system_score_gemma":0.002222246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007740184,"about_ca_topic_score_gemma":0.006868148,"domain_scores_codex":[0.9259631,0.06370023,0.004407235,0.002820709,0.002357883,0.0007507771],"domain_scores_gemma":[0.848347,0.09572858,0.01361039,0.03402735,0.007211571,0.001075133],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01718075,0.0008635436,0.4940401,0.003274374,0.02426878,0.001951737,0.002557906,0.08674467,0.001250718,0.01180483,0.06870542,0.2873572],"study_design_scores_gemma":[0.00794754,0.003912888,0.3714832,0.002456155,0.018679,0.002725848,0.001851674,0.4801289,0.003663566,0.06117976,0.04538031,0.000591276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4511286,0.006645488,0.4964264,0.004339424,0.0007529987,0.003053467,0.03325113,0.001862702,0.002539774],"genre_scores_gemma":[0.7895411,0.000938379,0.1792738,0.001032394,0.0001745852,0.003866409,0.02379578,0.0003479988,0.001029549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8867778,"threshold_uncertainty_score":0.5987831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09187554904669541,"score_gpt":0.3555831987871831,"score_spread":0.2637076497404877,"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."}}