{"id":"W4311522567","doi":"10.3390/diagnostics12123031","title":"Performance Evaluation of Different Object Detection Models for the Segmentation of Optical Cups and Discs","year":2022,"lang":"en","type":"article","venue":"Diagnostics","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Artificial intelligence; Computer science; Segmentation; Optic disc; Optic cup (embryology); Convolutional neural network; Glaucoma; Fundus (uterus); Computer vision; Pattern recognition (psychology); Object detection; Fundus photography; Point (geometry); Cascade; Encoder; Retinal; Mathematics; Ophthalmology; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0003432876,0.00004026486,0.0001006387,0.00003818984,0.00007617892,0.000003317707,0.00002233777,0.00000897513,0.000007712412],"category_scores_gemma":[0.0002808707,0.00002685261,0.0000382777,0.00007436838,0.00003496066,0.00002454548,0.00001967735,0.00004972178,6.686131e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003225228,"about_ca_system_score_gemma":0.00001852192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001200114,"about_ca_topic_score_gemma":0.000002163843,"domain_scores_codex":[0.9994152,0.00003340276,0.0001329535,0.00006712908,0.0003019047,0.00004942002],"domain_scores_gemma":[0.999308,0.0003984578,0.00006785651,0.00008090954,0.000130059,0.00001474428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005014693,0.0006859269,0.1485518,0.0004890453,0.0003665037,8.1719e-7,0.002827128,0.1783725,0.03729657,0.0004324994,0.0001899444,0.6302858],"study_design_scores_gemma":[0.0005598188,0.000310107,0.05665607,0.00002278772,0.0009435309,0.000003452104,0.0006729824,0.9057603,0.03483157,0.0002057279,0.000006125,0.00002754997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9819043,0.0002937586,0.01719349,0.0001931502,0.00004625511,0.000295353,0.000009725607,0.000003774083,0.00006025197],"genre_scores_gemma":[0.9992045,0.0003686406,0.0002464513,0.00001918913,0.00002218197,0.00009599391,0.00002410505,0.000004599597,0.00001435588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7273878,"threshold_uncertainty_score":0.1095017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03688216591071442,"score_gpt":0.3173543325428143,"score_spread":0.2804721666320999,"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."}}