{"id":"W3210191307","doi":"10.3390/curroncol28060366","title":"Assessment of Digital Pathology Imaging Biomarkers Associated with Breast Cancer Histologic Grade","year":2021,"lang":"en","type":"article","venue":"Current Oncology","topic":"AI in cancer detection","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; York University; University of Toronto; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; Association Canadienne des Technologues en Radiation Médicale; Terry Fox Research Institute","keywords":"Medicine; Grading (engineering); Receiver operating characteristic; Breast cancer; Convolutional neural network; Biopsy; Digital pathology; Radiology; Breast imaging; Pathology; Artificial intelligence; Mammography; Cancer; Computer science; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001962166,0.0001505025,0.0003220713,0.0001125558,0.00007281212,0.00003792054,0.0003756135,0.00007902693,0.00003810027],"category_scores_gemma":[0.00004762116,0.0001330424,0.0000689271,0.0005567624,0.0002184631,0.0003112305,0.000246508,0.0002337924,0.000002362172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001115718,"about_ca_system_score_gemma":0.0008630741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001067543,"about_ca_topic_score_gemma":0.00006356602,"domain_scores_codex":[0.9984801,0.0002057718,0.000281885,0.0004910666,0.0002196569,0.0003214797],"domain_scores_gemma":[0.9987785,0.0001710639,0.0003328181,0.0003370493,0.0003097095,0.00007084168],"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":[0.00001659526,0.0007804256,0.4794577,0.00003644759,0.0001295179,0.0003035867,0.0002166902,0.00009942107,0.001854167,0.001788512,0.001521037,0.5137959],"study_design_scores_gemma":[0.002752285,0.0005493714,0.9429308,0.0002253913,0.0001152248,0.001665403,0.0001869255,0.0320108,0.0009960027,0.002401782,0.01556694,0.0005990629],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4416457,0.006979708,0.5212229,0.01183282,0.01189619,0.0005231528,0.0002098259,0.0005265308,0.00516325],"genre_scores_gemma":[0.997672,0.0001396953,0.001948433,0.00007827083,0.00005640201,0.00005520158,0.00001850923,0.00001005222,0.00002147264],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5560263,"threshold_uncertainty_score":0.542531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05426329752397563,"score_gpt":0.3710435011301713,"score_spread":0.3167802036061956,"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."}}