{"id":"W4409944483","doi":"10.1016/j.jpi.2025.100426","title":"Erratum to “MiNuGAN: Dual segmentation of mitoses and nuclei using conditional GANs on multi-center breast H&E images” [Journal of Pathology Informatics Volume 13, 2022, 100002]","year":2025,"lang":"en","type":"erratum","venue":"Journal of Pathology Informatics","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Toronto Metropolitan University","funders":"Ryerson University","keywords":"Computer science; Center (category theory); Volume (thermodynamics); Segmentation; Dual (grammatical number); Informatics; Information retrieval; Artificial intelligence; Chemistry; Physics; Crystallography; Linguistics; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001995159,0.001989498,0.001437167,0.002813485,0.002875325,0.002641899,0.002611151,0.00492597,0.07487527],"category_scores_gemma":[0.02398746,0.001323517,0.001186795,0.001933267,0.002259842,0.001847122,0.001980662,0.006138321,0.03467679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002579377,"about_ca_system_score_gemma":0.002918382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0168121,"about_ca_topic_score_gemma":0.03730991,"domain_scores_codex":[0.9975175,0.0003805668,0.0003277684,0.0003358258,0.0013125,0.0001259522],"domain_scores_gemma":[0.9916471,0.002308754,0.0004698953,0.0006252691,0.004407572,0.00054132],"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":[0.00003423596,0.000005191577,0.00004390307,0.00005414723,0.000007615558,0.0001768739,0.00001581724,0.0001104551,0.0001558622,0.0006780689,0.9919921,0.006725769],"study_design_scores_gemma":[0.00005285902,0.00003224032,0.0005324234,0.0002284544,0.0000299566,0.0009330675,0.00006531147,0.002488936,0.001531974,0.002761906,0.9912724,0.00007041813],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0005036427,0.001849079,0.01483305,0.05294345,0.9146214,0.00006049313,0.002837908,0.003914326,0.008436761],"genre_scores_gemma":[0.02550419,0.009600217,0.0784265,0.1464676,0.236103,0.0004073069,0.01745187,0.01394534,0.4720941],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.07487527,"threshold_uncertainty_score":0.2504827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01795409713291108,"score_gpt":0.2833186146243428,"score_spread":0.2653645174914318,"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."}}