{"id":"W2341587220","doi":"10.1136/jclinpath-2015-202914","title":"Overview of contemporary guidelines in digital pathology: what is available in 2015 and what still needs to be addressed?","year":2015,"lang":"en","type":"review","venue":"Journal of Clinical Pathology","topic":"AI in cancer detection","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University Health Network","funders":"Medical Research Council","keywords":"Telepathology; Digital pathology; Medicine; Pathology; Virtual microscopy; Modalities; Telemedicine; Medical physics; Anatomical pathology; Computer science; Data science; Health care","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.008858819,0.0004395988,0.00463131,0.001104941,0.00001513027,0.000313194,0.001402562,0.0009694931,0.00002913114],"category_scores_gemma":[0.003454045,0.0003454508,0.0005566559,0.001060749,0.0002621522,0.004198875,0.0008744004,0.001459983,0.00004846736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001440816,"about_ca_system_score_gemma":0.002043257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009833354,"about_ca_topic_score_gemma":0.00001632172,"domain_scores_codex":[0.9914567,0.001073863,0.005909421,0.0006449573,0.0005343203,0.0003807619],"domain_scores_gemma":[0.9928539,0.001572951,0.003461765,0.0008182746,0.00087696,0.0004160906],"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":[0.00005450297,0.0001223623,0.0002095733,0.0009516694,0.00003423562,0.0009640971,0.0002666934,0.000002966153,3.347626e-7,0.000024702,0.0330401,0.9643288],"study_design_scores_gemma":[0.001023442,0.001380344,0.00004058351,0.01595284,0.00006171607,0.001571605,0.0001279866,0.00004589047,8.21163e-7,0.0009372661,0.9785629,0.0002946059],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003828941,0.9911911,0.0006397156,0.003290466,0.003892191,0.0004492006,0.00002060498,0.0000122394,0.0001215635],"genre_scores_gemma":[0.00006545978,0.9931663,0.003224703,0.002925799,0.0004016673,0.00001485617,0.000003477078,0.00003251799,0.0001652451],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9640341,"threshold_uncertainty_score":0.9998997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4023230932043617,"score_gpt":0.4980677162359687,"score_spread":0.09574462303160708,"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."}}