{"id":"W4402306899","doi":"10.18280/ts.410429","title":"Retinal Image Enhancement Through Hyperparameter Selection Using RSO for CLAHE to Classify Diabetic Retinopathy","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hyperparameter; Diabetic retinopathy; Adaptive histogram equalization; Selection (genetic algorithm); Computer science; Artificial intelligence; Retinal; Pattern recognition (psychology); Ophthalmology; Image (mathematics); Medicine; Histogram; Histogram equalization; Diabetes mellitus","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":[0.0005025786,0.0002676153,0.0003870442,0.0002021948,0.0001594868,0.0001761223,0.0000904381,0.00006985376,0.0007997374],"category_scores_gemma":[0.00005364313,0.0002257166,0.0003010356,0.0004916519,0.0000662711,0.0001668417,0.00003006082,0.0002300295,0.00009193347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000269419,"about_ca_system_score_gemma":0.0001015856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003337822,"about_ca_topic_score_gemma":0.000001728891,"domain_scores_codex":[0.9979222,0.00006573944,0.0004808962,0.0005895812,0.0004583115,0.0004832391],"domain_scores_gemma":[0.9993211,0.0001039775,0.00006622772,0.0001730761,0.0001758704,0.0001597699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004853679,0.0002881115,0.001766392,0.0006265801,0.0003619203,0.00006026803,0.00100733,0.0001168748,0.9738019,0.0002774258,0.009272766,0.01193503],"study_design_scores_gemma":[0.003075267,0.004935028,0.002863707,0.00277204,0.004073567,0.0002854863,0.0007310892,0.3591432,0.523774,0.001129763,0.09600135,0.001215448],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7141868,0.0002454036,0.2800888,0.003358728,0.0002378488,0.0007262342,0.00001516145,0.0001457528,0.0009953077],"genre_scores_gemma":[0.9357375,0.00001826174,0.06044525,0.001159508,0.0007410708,0.0001401921,0.00004364772,0.00005344606,0.001661111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4500279,"threshold_uncertainty_score":0.9204454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03614912443465586,"score_gpt":0.3325421939704948,"score_spread":0.296393069535839,"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."}}