{"id":"W3122731100","doi":"10.2196/24394","title":"Artificial Intelligence-based Segmentation of Nuclei in Multi-organ Histopathology Images: Model Development and Validation (Preprint)","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Preprint; Computer science; Segmentation; Histopathology; Artificial intelligence; Pathology; Medicine; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002859862,0.0005695766,0.0006447874,0.001135666,0.0005379697,0.001623193,0.001186042,0.001743747,0.001428832],"category_scores_gemma":[0.006339681,0.0005432407,0.001101536,0.0007006857,0.0008042054,0.0008501342,0.0006724918,0.0009715627,0.0004609881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001527518,"about_ca_system_score_gemma":0.001674567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02671447,"about_ca_topic_score_gemma":0.01404769,"domain_scores_codex":[0.9993938,0.0001915098,0.00003881307,0.000168637,0.0001565823,0.00005066961],"domain_scores_gemma":[0.9975731,0.001363816,0.0001668679,0.0002303339,0.0006227955,0.00004311673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001720144,0.0001424138,0.004952665,0.0001354145,0.00009902072,0.00004935203,0.0001280852,0.8958977,0.01062311,0.002021779,0.0007722895,0.08500613],"study_design_scores_gemma":[0.000003815712,0.00002464416,0.0009419791,0.000008276776,0.00001086631,0.00001781385,0.0000125042,0.9950304,0.003208421,0.0005735718,0.0001629938,0.000004783835],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2069231,0.0005197624,0.7866032,0.000579103,0.0001052237,0.0002479531,0.0004606056,0.001865813,0.002695131],"genre_scores_gemma":[0.787736,0.0002843639,0.2087857,0.0001083127,0.00002518708,0.0001710133,0.0007477644,0.000182819,0.00195881],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02671447,"threshold_uncertainty_score":0.05311793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05925210455671731,"score_gpt":0.3093555204203834,"score_spread":0.2501034158636661,"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."}}