{"id":"W4291020797","doi":"10.1089/neu.2022.0251","title":"Development and External Validation of a Machine Learning Model for the Early Prediction of Doses of Harmful Intracranial Pressure in Patients with Severe Traumatic Brain Injury","year":2022,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Traumatic Brain Injury and Neurovascular Disturbances","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Fonds Wetenschappelijk Onderzoek; Vlaamse regering; European Commission; ZNS - Hannelore Kohl Stiftung; KU Leuven; Integra LifeSciences","keywords":"Traumatic brain injury; Intracranial pressure; Medicine; Anesthesia; Intensive care medicine; Psychiatry","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":[],"consensus_categories":[],"category_scores_codex":[0.0005922454,0.000106102,0.0003565013,0.0001537463,0.00007267279,0.000006598032,0.0001128199,0.00002664382,0.00001494275],"category_scores_gemma":[0.0001493023,0.00007178405,0.00008624341,0.0001419973,0.00006760935,0.000138572,0.00002768639,0.000327021,1.855896e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001619104,"about_ca_system_score_gemma":0.0000846618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005897364,"about_ca_topic_score_gemma":0.000001846503,"domain_scores_codex":[0.9983563,0.0001309671,0.0007476233,0.0001085878,0.0005600539,0.00009650283],"domain_scores_gemma":[0.9987018,0.0002199073,0.0007894753,0.0001011567,0.0001514944,0.00003613444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03491441,0.003565578,0.6827373,0.003795938,0.001262441,0.00002315303,0.0378961,0.07763035,0.02702719,0.0001081519,0.0001162823,0.1309231],"study_design_scores_gemma":[0.006736225,0.004524998,0.9593944,0.0003750906,0.0003290638,0.0001123704,0.0003248846,0.0219402,0.00602338,0.00006610862,0.00009516307,0.00007810786],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970676,0.0001635553,0.001975218,0.0001291659,0.00006498723,0.0005381251,0.00005171745,0.000003395786,0.00000620243],"genre_scores_gemma":[0.9977928,0.00001380106,0.00208515,0.00003249623,0.00001977046,0.00001704471,0.000004315162,0.00001440376,0.00002019743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2766571,"threshold_uncertainty_score":0.2927269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0399810944324326,"score_gpt":0.2690211610958375,"score_spread":0.2290400666634049,"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."}}