{"id":"W3175939954","doi":"10.1096/fasebj.2019.33.1_supplement.444.30","title":"Learning through the Eyes of the Beholder: Using Eye Tracking to Understand How Novices Learn Neuroanatomy","year":2019,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Anatomy and Medical Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Neuroanatomy; Contrast (vision); Coronal plane; Eye tracking; Psychology; Tracking (education); Cognitive psychology; Computer science; Neuroscience; Artificial intelligence; Medicine; Anatomy","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":[0.0003934407,0.0001258777,0.0001677021,0.00004415135,0.0003466121,0.00006825967,0.0005734731,0.0000829753,0.0000593038],"category_scores_gemma":[0.00009887949,0.00006058126,0.0001101733,0.0002863255,0.0001563028,0.0001499251,0.00009328022,0.001151155,0.000008331351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004648049,"about_ca_system_score_gemma":0.00003304391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001815327,"about_ca_topic_score_gemma":0.00001189535,"domain_scores_codex":[0.9990349,0.000106105,0.0001791069,0.00009458852,0.0002924233,0.0002929191],"domain_scores_gemma":[0.9994226,0.00014649,0.0001013959,0.0002467484,0.00003643422,0.0000463894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009435591,0.00008637427,0.02312884,0.0002731225,0.0008844191,0.00008284681,0.05074961,0.561552,0.2538895,0.01296724,0.001732749,0.09455895],"study_design_scores_gemma":[0.004051176,0.00103288,0.009507986,0.0017865,0.000779753,0.002111116,0.2783502,0.2036391,0.2932195,0.01508837,0.1887899,0.00164351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987705,0.0008687575,0.005562556,0.00383082,0.0004960363,0.0001448462,9.056861e-7,0.00006200431,0.001329093],"genre_scores_gemma":[0.9990438,0.0001939058,0.0001254439,0.0002664529,0.0001194933,6.353036e-7,1.363386e-7,0.00002409472,0.0002260014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3579129,"threshold_uncertainty_score":0.5001262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0209770774382924,"score_gpt":0.2528681369113144,"score_spread":0.231891059473022,"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."}}