{"id":"W3132659672","doi":"","title":"Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part V (biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology)","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia; Canada Research Chairs; University of Toronto","funders":"","keywords":"Normalization (sociology); Computer science; Histopathology; Stain; Segmentation; Artificial intelligence; Computer vision; Pathology; Medicine; Staining","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":[0.003096286,0.001474716,0.001238242,0.002244058,0.0006567326,0.002206655,0.001364258,0.001439398,0.02657173],"category_scores_gemma":[0.003067663,0.0005297142,0.0006048621,0.001919331,0.001045097,0.001571926,0.001838052,0.001504707,0.01260518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00142628,"about_ca_system_score_gemma":0.002880151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01108129,"about_ca_topic_score_gemma":0.01012614,"domain_scores_codex":[0.9990895,0.0002024784,0.00004780945,0.0001867917,0.0003555896,0.0001179],"domain_scores_gemma":[0.9984919,0.0002836458,0.00003516835,0.0001355211,0.0007814913,0.000272221],"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":[0.0004172538,0.0002227273,0.0006480481,0.0003821106,0.00008607061,0.00008204524,0.0000591843,0.002796076,0.006400103,0.008457378,0.6515766,0.3288724],"study_design_scores_gemma":[0.00009849885,0.0002584592,0.01066516,0.0002869611,0.0001064346,0.0005124486,0.0001231695,0.06439205,0.01627744,0.01336853,0.8938351,0.00007577983],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.04324581,0.160201,0.4505421,0.03679467,0.05607421,0.001191039,0.0129675,0.01684666,0.2221371],"genre_scores_gemma":[0.09517257,0.06295733,0.2092525,0.001967819,0.00880507,0.0009110188,0.02339205,0.003866138,0.5936756],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02657173,"threshold_uncertainty_score":0.08889127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440683152857515,"score_gpt":0.2623743718655274,"score_spread":0.2479675403369523,"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."}}