{"id":"W4220853026","doi":"10.1109/icais53314.2022.9742893","title":"Retinal Vessel Segmentation Techniques","year":2022,"lang":"en","type":"article","venue":"2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS)","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Retinal; Computer science; Fundus (uterus); Categorization; Artificial intelligence; Contrast (vision); Segmentation; Computer vision; Retina; Image segmentation; Feature extraction; Medicine; Ophthalmology; Biology; Neuroscience","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":[0.0009407516,0.0008222579,0.0008561686,0.004261874,0.0007057209,0.001957592,0.0009882814,0.00152577,0.005409552],"category_scores_gemma":[0.001458852,0.0007316794,0.001221846,0.002967637,0.0005182141,0.001472216,0.000713577,0.001227958,0.004336735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007470186,"about_ca_system_score_gemma":0.001036728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002625606,"about_ca_topic_score_gemma":0.002902639,"domain_scores_codex":[0.9991189,0.0001046243,0.00006060059,0.0002933791,0.0003418787,0.00008061763],"domain_scores_gemma":[0.9993481,0.000176264,0.00007408598,0.0001278666,0.0002458036,0.00002789026],"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":[0.0001288778,0.00004074548,0.001329127,0.000693405,0.00009144645,0.0002881721,0.0002225021,0.004352919,0.05896448,0.008360334,0.008600542,0.9169273],"study_design_scores_gemma":[0.0001021836,0.0005031469,0.01349619,0.0007830185,0.0006234444,0.01105355,0.0003908126,0.1867328,0.2963002,0.0267914,0.4630036,0.0002195658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01732944,0.02923656,0.923257,0.0008905719,0.0004548687,0.0002889196,0.0004153523,0.003776196,0.02435105],"genre_scores_gemma":[0.1087332,0.02770539,0.8376886,0.0008065838,0.0005191467,0.0002159396,0.001115586,0.0007839516,0.02243157],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005409552,"threshold_uncertainty_score":0.01809669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05671590479451059,"score_gpt":0.3243971121747313,"score_spread":0.2676812073802207,"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."}}