{"id":"W4367841510","doi":"10.32920/22734380","title":"A novel Accelerated Greedy Snake Algorithm for active contours","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Convergence (economics); Algorithm; Greedy algorithm; Object (grammar); Pixel; Similarity (geometry); Relaxation (psychology); Computer science; Mathematics; Artificial intelligence; Mathematical optimization; Image (mathematics)","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":[0.0006485083,0.0008270796,0.000946856,0.001023522,0.0004337125,0.0008778513,0.001597839,0.001429193,0.002603594],"category_scores_gemma":[0.001057267,0.0006293008,0.001085743,0.001192328,0.0006029719,0.001154436,0.001142098,0.001256869,0.00134474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003507581,"about_ca_system_score_gemma":0.0008094126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009609043,"about_ca_topic_score_gemma":0.001014195,"domain_scores_codex":[0.9994516,0.0001052334,0.00002386662,0.0001003001,0.0002809507,0.00003809961],"domain_scores_gemma":[0.9997106,0.00009335475,0.00002660366,0.00004025605,0.0001042609,0.00002488277],"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":[0.0001837783,0.00008614371,0.000584413,0.0003155048,0.0001223307,0.000354644,0.0001790229,0.2204586,0.06754295,0.05268983,0.0116737,0.6458092],"study_design_scores_gemma":[0.0000363106,0.00006375877,0.0001469227,0.00001848998,0.00001957818,0.0003423709,0.00001275369,0.9600828,0.00763727,0.01082904,0.02078235,0.00002842945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001074152,0.0001723662,0.9977355,0.0000518379,0.00004552179,0.00002106238,0.00001218443,0.0003317112,0.0005557217],"genre_scores_gemma":[0.03406772,0.0003508482,0.9622975,0.0001202737,0.00007112866,0.0001222974,0.000120442,0.0002088139,0.002640983],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002603594,"threshold_uncertainty_score":0.008709908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1249915989577709,"score_gpt":0.3696387095472299,"score_spread":0.2446471105894589,"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."}}