{"id":"W2616587551","doi":"10.1017/cem.2017.330","title":"P128: The novel application of eye-tracking for the cognitive task analysis of expert physician decision-making while leading real-world traumatic resuscitations","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Clinical Reasoning and Diagnostic Skills","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Debriefing; Eye tracking; Cognition; Task (project management); Protocol analysis; Recall; Protocol (science); Medicine; Think aloud protocol; Variety (cybernetics); Psychology; Applied psychology; Computer science; Medical education; Human–computer interaction; Cognitive psychology; Artificial intelligence; Psychiatry; Cognitive science; Usability","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006162349,0.0004740777,0.0002682705,0.0007192324,0.0003283782,0.0009809588,0.0005277233,0.0008943872,0.004757098],"category_scores_gemma":[0.00467238,0.0001785105,0.000219914,0.0006624534,0.0002138464,0.0006465461,0.0008862401,0.0005411885,0.001463378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002553407,"about_ca_system_score_gemma":0.0008019025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004396442,"about_ca_topic_score_gemma":0.007972197,"domain_scores_codex":[0.9996557,0.00007608612,0.00001599374,0.00008684926,0.0001290219,0.00003633272],"domain_scores_gemma":[0.9990628,0.0004580603,0.00007307006,0.00008089012,0.0002614631,0.00006364883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001460383,0.0003834425,0.01938358,0.0004259152,0.0001214734,0.0008250455,0.001009795,0.004305195,0.2053284,0.001976441,0.0208741,0.7439061],"study_design_scores_gemma":[0.0006292107,0.001609783,0.2486414,0.0004971483,0.0003293455,0.007836575,0.001203838,0.4674816,0.1961246,0.02025024,0.05492399,0.0004721392],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5927402,0.002127596,0.3447784,0.00278679,0.001421918,0.001069918,0.005907016,0.00524025,0.04392788],"genre_scores_gemma":[0.8179536,0.0006474603,0.172389,0.0006701294,0.0003252308,0.0003215897,0.0009173006,0.0003312246,0.006444427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004757098,"threshold_uncertainty_score":0.01591408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1465108396222113,"score_gpt":0.4724967543027614,"score_spread":0.3259859146805501,"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."}}