{"id":"W4389449631","doi":"10.1212/wnl.94.15_supplement.5350","title":"Video-based Eye Tracking Distinguishes Follow Up OMAS Patients from Controls (5350)","year":2020,"lang":"en","type":"article","venue":"Neurology","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Hospital for Sick Children","funders":"","keywords":"Medicine; Artificial intelligence; Ophthalmology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001667381,0.0003373358,0.0002467177,0.0007990409,0.0003373105,0.0003746915,0.0001710952,0.0003590779,0.002560128],"category_scores_gemma":[0.0007999906,0.00009809453,0.0001682541,0.0004141961,0.0001178938,0.0002519788,0.0002280485,0.0002148207,0.000539035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000213036,"about_ca_system_score_gemma":0.00009321355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005048587,"about_ca_topic_score_gemma":0.006445601,"domain_scores_codex":[0.9998829,0.00001287704,0.00001654056,0.00003635131,0.00002141077,0.0000298325],"domain_scores_gemma":[0.9997039,0.00005904449,0.0001036545,0.00002338097,0.00005236726,0.00005762443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00144224,0.0002262582,0.9615223,0.00002331037,0.00006345075,0.0008432005,0.0002019155,0.00005554381,0.01878131,0.00005215455,0.0003306274,0.01645765],"study_design_scores_gemma":[0.00001542102,0.000469679,0.9973758,0.000003893022,0.00002230337,0.001050624,0.00007830612,0.0001184762,0.0006687752,0.00001660613,0.0001772811,0.000002737902],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992749,0.00009622292,0.0000622537,0.000007345468,0.000004783207,0.000005643762,0.0001156972,0.000006433036,0.0004267044],"genre_scores_gemma":[0.9991079,0.00004104641,0.00007498344,0.00001522568,0.000003819688,0.000007368936,0.000283722,0.000002706001,0.0004631581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005048587,"threshold_uncertainty_score":0.01003838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02119466816620231,"score_gpt":0.2384023332749365,"score_spread":0.2172076651087342,"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."}}