{"id":"W2801242194","doi":"10.1016/j.annemergmed.2018.03.005","title":"Getting Inside the Expert’s Head: An Analysis of Physician Cognitive Processes During Trauma Resuscitations","year":2018,"lang":"en","type":"article","venue":"Annals of Emergency Medicine","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Queen's University; Universiteit Maastricht","keywords":"Medicine; Cognition; Eye tracking; Neurocognitive; Medical emergency; Psychiatry; Computer science; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005179372,0.0001578324,0.0004828653,0.0005437261,0.0002211655,0.000001530637,0.0001338169,0.0000590118,0.001042197],"category_scores_gemma":[0.002048885,0.000112177,0.0001248175,0.002798329,0.0003325274,0.0001498869,0.00001370693,0.0001229466,0.000003920411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001754936,"about_ca_system_score_gemma":0.0002261267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001695291,"about_ca_topic_score_gemma":0.0006458253,"domain_scores_codex":[0.9978395,0.0001296272,0.0009660703,0.0002889866,0.0005259588,0.0002498508],"domain_scores_gemma":[0.9937389,0.0005503009,0.0005226997,0.0004292467,0.004600665,0.0001581896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001061633,0.001278894,0.677637,0.002001656,0.003189268,0.000003536999,0.2830881,0.0004573082,0.01766993,0.0004750961,0.005885189,0.007252438],"study_design_scores_gemma":[0.0005984748,0.0008196699,0.9197097,0.0008334725,0.0008689183,6.744531e-7,0.05185303,0.001031752,0.02373768,0.0002876138,0.0001282938,0.0001307542],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9837669,0.001555151,0.00009055495,0.0120996,0.0004638879,0.0003958167,0.00002606264,0.00003536979,0.00156673],"genre_scores_gemma":[0.9968342,0.0002794201,0.00007793037,0.001266037,0.001209092,0.00004502621,0.0001503528,0.00002123558,0.0001167723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2420727,"threshold_uncertainty_score":0.999871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2614929813648904,"score_gpt":0.5124813603313442,"score_spread":0.2509883789664538,"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."}}