{"id":"W4409449502","doi":"10.1016/j.semdp.2025.150905","title":"An adapted & improved validation protocol for digital pathology implementation","year":2025,"lang":"en","type":"review","venue":"Seminars in Diagnostic Pathology","topic":"AI in cancer detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"","keywords":"Digital pathology; Pathology; Protocol (science); Computer science; Medicine","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"],"consensus_categories":[],"category_scores_codex":[0.0009535468,0.0005666252,0.00129017,0.0007868166,0.0001220562,0.0001749262,0.001332582,0.0007108155,0.00001892529],"category_scores_gemma":[0.002733577,0.0005715654,0.0002582529,0.0008891844,0.0001004762,0.0006531731,0.0003723486,0.0004447315,0.00002511562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005397027,"about_ca_system_score_gemma":0.000765333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000989982,"about_ca_topic_score_gemma":0.00006955338,"domain_scores_codex":[0.9958054,0.0006001494,0.001332779,0.001416001,0.0001891004,0.000656617],"domain_scores_gemma":[0.9932663,0.004334897,0.0008644128,0.001278553,0.0001645702,0.00009120531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001119845,0.0001237432,0.00003481827,0.00344677,0.00001330974,0.00006753961,0.0001514731,0.000007864332,0.00000768233,0.0004818495,0.000610526,0.9950432],"study_design_scores_gemma":[0.001698528,0.001294515,0.00003633438,0.009259953,0.0001679542,0.0005019979,0.00003521805,0.0003633082,0.00008700374,0.005977761,0.9796455,0.000931926],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.000008279735,0.2286276,0.5428628,0.00008870006,0.001530513,0.2260233,0.0003508686,0.0003595553,0.0001483835],"genre_scores_gemma":[0.000007655368,0.3491614,0.02320334,0.00007309524,0.0001709367,0.6265108,0.0007554056,0.00004945237,0.00006792572],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.9941113,"threshold_uncertainty_score":0.9996736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04618372960825541,"score_gpt":0.4162019781658773,"score_spread":0.3700182485576219,"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."}}