{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005353156,0.00280931,0.002237145,0.004591117,0.003073856,0.00417851,0.003652197,0.006129894,0.07210442],"category_scores_gemma":[0.1098348,0.001333913,0.001825355,0.00274138,0.003350096,0.002198959,0.00237792,0.009473284,0.05317535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003789956,"about_ca_system_score_gemma":0.005585371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02238355,"about_ca_topic_score_gemma":0.01896589,"domain_scores_codex":[0.9933239,0.0009934048,0.001259695,0.001020292,0.003045706,0.0003570033],"domain_scores_gemma":[0.9482679,0.0108983,0.002390025,0.003091104,0.03364541,0.001707352],"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":[0.00002621378,0.000003251367,0.00004115355,0.0001101226,0.000009377203,0.0002655147,0.00002726142,0.00003417836,0.00004534167,0.0004586989,0.9934844,0.00549461],"study_design_scores_gemma":[0.00003779593,0.00001877478,0.0003555125,0.0003274415,0.0000385758,0.001151959,0.00005943213,0.0003405144,0.0004898062,0.001144779,0.9959962,0.00003912995],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001630926,0.001089902,0.002177594,0.04790759,0.9427958,0.00003963211,0.002538198,0.0009265795,0.002361676],"genre_scores_gemma":[0.02609024,0.01330444,0.01843151,0.1167729,0.4589809,0.0005171878,0.01050337,0.006488353,0.3489111],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.07210442,"threshold_uncertainty_score":0.2412133,"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."}}