{"id":"W4395036406","doi":"10.1055/s-0044-1784028","title":"Eye-Tracker-basierte Differenzierung von Schwindelursachen: Eine mobile Möglichkeit der schnelleren und genaueren Triagierung im Notfall","year":2024,"lang":"de","type":"article","venue":"Laryngo-Rhino-Otologie","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science","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":["metaepi_narrow","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.00160848,0.002128889,0.002367877,0.001703366,0.001064964,0.00213152,0.005479381,0.002308148,0.000511249],"category_scores_gemma":[0.0006309034,0.001935185,0.001055721,0.003410507,0.001229538,0.001364506,0.002636372,0.004111897,0.005735668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009487467,"about_ca_system_score_gemma":0.001033551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005325759,"about_ca_topic_score_gemma":0.0001479943,"domain_scores_codex":[0.9877041,0.000861294,0.00212077,0.004307417,0.001422704,0.003583741],"domain_scores_gemma":[0.9929066,0.001302416,0.0006190997,0.003872074,0.0004757417,0.0008241009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009919242,0.005058575,0.07090722,0.003497187,0.01556074,0.01341852,0.005448498,0.001460046,0.0379149,0.1179378,0.07073133,0.6570733],"study_design_scores_gemma":[0.01032994,0.00567349,0.1589226,0.004311177,0.007410647,0.0005009925,0.0005925372,0.2080745,0.04051647,0.02806304,0.5247186,0.01088602],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6787202,0.2368946,0.04330723,0.01298659,0.01284753,0.003679504,0.0004543943,0.008453456,0.002656484],"genre_scores_gemma":[0.9811394,0.00321383,0.00834885,0.000834135,0.001586117,0.0005611511,0.0002270123,0.0003051148,0.003784403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6461872,"threshold_uncertainty_score":0.9999015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02596355219954072,"score_gpt":0.3119337665643314,"score_spread":0.2859702143647906,"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."}}