{"id":"W7161681486","doi":"10.1109/imtic68267.2025.11520534","title":"Optimizing Retinal Vessel Segmentation Performance Through a Systematic Comparison of Modified U-Net Variants","year":2025,"lang":"","type":"article","venue":"","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Segmentation; Pattern recognition (psychology); Image segmentation; Retinal; Noise (video)","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":[0.00235519,0.001592053,0.001381146,0.001748428,0.0006308405,0.001604738,0.001944184,0.001336204,0.002095455],"category_scores_gemma":[0.007720108,0.0005800289,0.0009330426,0.001345878,0.0003896566,0.001690848,0.000848971,0.0008998536,0.0006691971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001005049,"about_ca_system_score_gemma":0.001789067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01209239,"about_ca_topic_score_gemma":0.01637329,"domain_scores_codex":[0.9987419,0.0002755532,0.0001265201,0.0003344806,0.000398868,0.0001226684],"domain_scores_gemma":[0.9967754,0.001799929,0.0001733475,0.0003313736,0.0008296157,0.00009027142],"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":[0.002857514,0.0004783699,0.007230458,0.0009459799,0.0007457093,0.0002716431,0.00009791703,0.2655221,0.01973242,0.00280529,0.007347823,0.6919647],"study_design_scores_gemma":[0.000122981,0.0004856364,0.002729964,0.00005827812,0.0002670243,0.0002324678,0.00005587261,0.9762636,0.01685888,0.001094856,0.001798508,0.00003191252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5112864,0.01475051,0.4510045,0.0005277364,0.0006090113,0.0004584625,0.001317836,0.01135824,0.008687325],"genre_scores_gemma":[0.6676217,0.002214526,0.3226182,0.0002136195,0.000101313,0.0001852133,0.002607529,0.001825229,0.002612722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01209239,"threshold_uncertainty_score":0.02404398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03382809012064963,"score_gpt":0.3419643659066566,"score_spread":0.308136275786007,"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."}}