{"id":"W3011545441","doi":"10.1111/ajt.15850","title":"Banff Digital Pathology Working Group: Going digital in transplant pathology","year":2020,"lang":"en","type":"article","venue":"American Journal of Transplantation","topic":"AI in cancer detection","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Institute of Biomedical Imaging and Bioengineering; National Cancer Institute","keywords":"Digital pathology; Medicine; Standardization; Pathology; Medical physics; Computer science","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":[0.05088819,0.001017456,0.0009272255,0.00741646,0.004364928,0.01225807,0.004252578,0.01045967,0.04957576],"category_scores_gemma":[0.05361303,0.0007997223,0.0008985992,0.00460527,0.003928102,0.01188988,0.01299729,0.009742741,0.03485434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004113843,"about_ca_system_score_gemma":0.0227672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004581839,"about_ca_topic_score_gemma":0.006138772,"domain_scores_codex":[0.9844217,0.004843208,0.001604384,0.001202499,0.005572548,0.002355481],"domain_scores_gemma":[0.8895863,0.01812441,0.005511892,0.00771124,0.03422036,0.04484578],"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":[0.00004284671,0.00005751673,0.001200311,0.0001514178,0.000004518595,0.000103038,0.0001623584,0.00005293664,0.0003892289,0.003354457,0.8816765,0.1128048],"study_design_scores_gemma":[0.00001470226,0.00003343337,0.001201814,0.0005872803,0.000005267937,0.0002245001,0.0003581734,0.00008264231,0.0002658837,0.003790127,0.9934146,0.00002162688],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00375801,0.02971501,0.01863364,0.772832,0.08204705,0.001172739,0.002309201,0.002745701,0.08678671],"genre_scores_gemma":[0.03830393,0.06745613,0.09767636,0.3843827,0.09552898,0.003386874,0.01995007,0.003619873,0.289695],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.05088819,"threshold_uncertainty_score":0.2691257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01171921236308909,"score_gpt":0.2185402422464946,"score_spread":0.2068210298834055,"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."}}