{"id":"W4405364447","doi":"10.1101/2024.02.19.23300472","title":"Automated visual acuity estimation by optokinetic nystagmus using a stepped sweep stimulus","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Health Research Council of New Zealand; Hong Kong Government","keywords":"Optokinetic reflex; Nystagmus; Stimulus (psychology); Audiology; Computer vision; Visual acuity; Computer science; Artificial intelligence; Psychology; Eye movement; Medicine; Ophthalmology; Cognitive psychology","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":[0.0004666209,0.000289509,0.0003392813,0.0006836347,0.0001070236,0.0003221102,0.0002963408,0.0002160477,0.001706902],"category_scores_gemma":[0.001280906,0.0001123924,0.0001550597,0.0003085648,0.0001446126,0.000256107,0.0002960062,0.000148872,0.0003860625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001847773,"about_ca_system_score_gemma":0.0002066361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001091214,"about_ca_topic_score_gemma":0.00224474,"domain_scores_codex":[0.9995549,0.0001195657,0.00003506318,0.0001195415,0.0001454649,0.00002538098],"domain_scores_gemma":[0.9992899,0.0002398859,0.00009587784,0.00007951699,0.0002556759,0.00003921179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002318461,0.000371332,0.1367159,0.0003896419,0.000142106,0.0001756263,0.0002133595,0.001781636,0.6410151,0.0002282006,0.001140046,0.2155086],"study_design_scores_gemma":[0.0001609091,0.001812336,0.7789255,0.00005719081,0.0000872653,0.001199447,0.0001269286,0.03529231,0.1805114,0.0001865393,0.001558764,0.00008138008],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9681819,0.0002183605,0.0286234,0.00001620372,0.00002140607,0.0002330948,0.0007529403,0.0005731675,0.001379519],"genre_scores_gemma":[0.9511774,0.0001313777,0.04714146,0.00003308504,0.00001368685,0.0002408663,0.0004464364,0.0000409817,0.0007747643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001706902,"threshold_uncertainty_score":0.005710125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0640433419901961,"score_gpt":0.3821447342154726,"score_spread":0.3181013922252764,"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."}}