{"id":"W4417132354","doi":"10.1109/tiptekno68206.2025.11270202","title":"AI Assisted Polyp Detection and Segmentation in Colonoscopy","year":2025,"lang":"","type":"article","venue":"","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Dice; Segmentation; Pipeline (software); Pattern recognition (psychology); Deep learning; Image segmentation; Encoder; Sørensen–Dice coefficient; Test set","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":[0.0004405966,0.000612719,0.0004260127,0.0008529644,0.0002591723,0.0008906547,0.0007788891,0.0008828073,0.002500947],"category_scores_gemma":[0.001523328,0.0005360515,0.0003813212,0.0004349186,0.0001962801,0.0006070464,0.0007319573,0.0005131952,0.001333594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005553116,"about_ca_system_score_gemma":0.0007816583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004947004,"about_ca_topic_score_gemma":0.01012002,"domain_scores_codex":[0.9997231,0.00004997992,0.0000134805,0.00008609606,0.0000895465,0.00003777377],"domain_scores_gemma":[0.9996946,0.0001289272,0.00002859227,0.00003451558,0.00008177286,0.00003169346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001023393,0.0001401122,0.004502365,0.0003318027,0.00009979535,0.0006314221,0.0001792022,0.04218292,0.1876321,0.001541757,0.006077849,0.7556573],"study_design_scores_gemma":[0.00003926299,0.0002335967,0.004956541,0.00003228845,0.00004826778,0.00107093,0.0000523143,0.9144866,0.07050323,0.00168816,0.006838102,0.00005071297],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1244965,0.002340941,0.8517277,0.0007067527,0.0001593817,0.0001820069,0.0005185117,0.0145221,0.005346173],"genre_scores_gemma":[0.5217925,0.0007446438,0.46931,0.0005162588,0.00008823341,0.0001175899,0.0006002041,0.0004202446,0.006410201],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004947004,"threshold_uncertainty_score":0.009836435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01171950105259755,"score_gpt":0.3106984076587648,"score_spread":0.2989789066061673,"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."}}