{"id":"W4396580378","doi":"10.3390/diagnostics14090900","title":"Correction: Raymann, J.; Rajalakshmi, R. GAR-Net: Guided Attention Residual Network for Polyp Segmentation from Colonoscopy Video Frames. Diagnostics 2023, 13, 123","year":2024,"lang":"en","type":"erratum","venue":"Diagnostics","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Residual; Colonoscopy; Segmentation; Computer science; Artificial intelligence; Medicine; Colorectal cancer; Internal medicine; Algorithm; Cancer","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0005095419,0.0009249597,0.001283323,0.00040728,0.0004716005,0.0003495198,0.0002710804,0.001749938,0.0002993889],"category_scores_gemma":[0.005834199,0.000992718,0.0005681774,0.0008737006,0.0001726456,0.0001537305,0.0001830812,0.002174602,0.0004623787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00100577,"about_ca_system_score_gemma":0.0009186139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001671519,"about_ca_topic_score_gemma":0.002954224,"domain_scores_codex":[0.9952058,0.0001721676,0.001284751,0.001409815,0.001016909,0.0009105179],"domain_scores_gemma":[0.9932855,0.00405112,0.000687818,0.0008190799,0.0007617774,0.0003946488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002396229,0.0001711964,0.0029377,0.0004349193,0.0006341297,0.0001501941,0.0001948239,0.0004004892,0.00002958292,0.0000141151,0.9870565,0.005580127],"study_design_scores_gemma":[0.003181152,0.00657711,0.02374755,0.006707238,0.004971484,0.00008659247,0.0003210515,0.009096986,0.0006923932,0.001258062,0.9420574,0.001302972],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.01791129,0.1322209,0.04841609,0.007146282,0.755787,0.01173833,0.006287326,0.002593954,0.01789885],"genre_scores_gemma":[0.01499661,0.1100913,0.01686688,0.007509775,0.1809544,0.006069914,0.1274488,0.001583788,0.5344787],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.5748326,"threshold_uncertainty_score":0.999546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02034127713322563,"score_gpt":0.3016070326807709,"score_spread":0.2812657555475453,"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."}}