{"id":"W2949373197","doi":"10.15407/kvt195.01.064","title":"The System of Intraocular Pressure Assessment Using Interference Eye Pictures","year":2019,"lang":"en","type":"article","venue":"Cybernetics and computer engineering","topic":"Glaucoma and retinal disorders","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"ASTER","funders":"","keywords":"Intraocular pressure; Optometry; Ophthalmology; Interference (communication); Computer science; Medicine; Telecommunications; Channel (broadcasting)","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":[0.001322617,0.001372538,0.0009750224,0.00625527,0.000701149,0.001831461,0.001063024,0.00100891,0.008758477],"category_scores_gemma":[0.003408727,0.0003853391,0.000698701,0.002771039,0.0003706195,0.001360258,0.00181396,0.0006559023,0.0065122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006406866,"about_ca_system_score_gemma":0.0009803608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003158252,"about_ca_topic_score_gemma":0.002868622,"domain_scores_codex":[0.9973883,0.0005044705,0.0002894174,0.0005044989,0.001218457,0.00009484073],"domain_scores_gemma":[0.9984733,0.0002134419,0.0001836799,0.00009687764,0.0009582778,0.00007438577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001442684,0.000228908,0.0946415,0.001753369,0.0003340385,0.0009290599,0.0005385859,0.00178716,0.06250659,0.00441284,0.04026338,0.7911619],"study_design_scores_gemma":[0.0008586526,0.003201064,0.4821689,0.001287094,0.001413447,0.02464004,0.001265156,0.1014343,0.1275475,0.007930787,0.2469663,0.00128676],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1661444,0.02138088,0.6115664,0.001594652,0.002212466,0.006627587,0.03832221,0.03050676,0.1216448],"genre_scores_gemma":[0.5654287,0.009608006,0.3693045,0.001119591,0.0006651784,0.005172074,0.01540746,0.0006700807,0.03262449],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008758477,"threshold_uncertainty_score":0.02930003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004342663798651365,"score_gpt":0.2160331637671412,"score_spread":0.2116904999684898,"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."}}