{"id":"W4308560904","doi":"10.1093/sleepadvances/zpac029.063","title":"O064 A Portable Ocular Assessment for Predicting Fitness to Drive under Extended-Wakefulness Conditions – Preliminary Analysis","year":2022,"lang":"en","type":"article","venue":"SLEEP Advances","topic":"Sleep and Work-Related Fatigue","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"NeuroRx Research (Canada)","funders":"","keywords":"Wakefulness; Alertness; Latency (audio); Simulation; Simulator sickness; Driving simulator; Headset; Medicine; Eye movement; Audiology; Psychology; Physical medicine and rehabilitation; Computer science; Virtual reality; Ophthalmology; Neuroscience; Artificial intelligence","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":[0.0006803494,0.0004099462,0.0001617622,0.0004018638,0.0001462874,0.0003149351,0.0002189791,0.0002538762,0.002724409],"category_scores_gemma":[0.001379874,0.0001335931,0.0003346536,0.0001830727,0.0001158754,0.0002152864,0.0003052677,0.0001636796,0.0005726675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001351806,"about_ca_system_score_gemma":0.000170945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003946001,"about_ca_topic_score_gemma":0.008334722,"domain_scores_codex":[0.9997402,0.00007394214,0.00002745913,0.00004781349,0.00008351427,0.00002712871],"domain_scores_gemma":[0.9991824,0.0002797741,0.0001321592,0.00005549863,0.000239966,0.0001100951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001824686,0.0004773838,0.9534701,0.00005725287,0.000129277,0.0001017148,0.00015077,0.0004374274,0.01210874,0.00002326406,0.0003906478,0.03082886],"study_design_scores_gemma":[0.0000227352,0.001501378,0.996431,0.000003447087,0.00001986134,0.00007623219,0.00007351887,0.0009917115,0.0007121367,0.000007622255,0.0001561447,0.000004161542],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983464,0.00003036827,0.0005957301,0.000008640341,0.000003701175,0.00007094251,0.0004049141,0.00001436701,0.000524883],"genre_scores_gemma":[0.9974234,0.00002526469,0.001197474,0.00001310345,0.000005399871,0.00007712607,0.0007076986,0.000003601738,0.0005469203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003946001,"threshold_uncertainty_score":0.009114027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0150921779129568,"score_gpt":0.3430696438558468,"score_spread":0.32797746594289,"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."}}