{"id":"W2057614943","doi":"10.5539/cis.v7n2p48","title":"Automatic Exudate Detection Using Eye Fundus Image Analysis Due to Diabetic Retinopathy","year":2014,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diabetic retinopathy; Blindness; Fundus (uterus); Diabetes mellitus; Computer science; Retinopathy; Medicine; Ophthalmology; Robustness (evolution); Exudate; Retina; Segmentation; Artificial intelligence; Disease; Optometry; Computer vision; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000796172,0.00008576484,0.0002127562,0.0008658824,0.0002387329,0.0003247807,0.0001009173,0.00001918393,0.00001522179],"category_scores_gemma":[0.000118253,0.00006959343,0.00005730373,0.002202559,0.0001338608,0.001822786,0.00007736289,0.00006667413,0.00005265853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004125867,"about_ca_system_score_gemma":0.00002927818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002201326,"about_ca_topic_score_gemma":4.65907e-7,"domain_scores_codex":[0.9990294,0.00002557938,0.0002788129,0.0001545431,0.0003279,0.0001837725],"domain_scores_gemma":[0.9992293,0.00002337619,0.00009785779,0.0002262053,0.0002423845,0.0001808458],"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":[0.00001798515,0.0000361427,0.02787762,0.0001876914,0.0001012497,0.000004075037,0.003175379,0.003182862,0.02602677,0.0001179656,0.0000559513,0.9392163],"study_design_scores_gemma":[0.0001237943,0.0000644711,0.1680781,0.00002951304,0.0001491108,0.00001953373,0.00003679575,0.8290708,0.002070718,0.0000124794,0.0002705563,0.00007417796],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5692025,0.000002530552,0.4301313,0.0001521659,0.00005637978,0.00004962456,4.264644e-7,0.0000357622,0.0003692724],"genre_scores_gemma":[0.9741395,0.000002029139,0.02488926,0.0009020737,0.0000474693,0.000002111747,0.000004066824,0.000002162619,0.00001140266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9391421,"threshold_uncertainty_score":0.3131868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009447266925741753,"score_gpt":0.2760248092250483,"score_spread":0.2665775422993065,"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."}}