{"id":"W4200124817","doi":"10.1109/bibe52308.2021.9635177","title":"Learning Similarity via Subjective Evaluations and Deep Features of Histopathology Images","year":2021,"lang":"en","type":"article","venue":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Similarity (geometry); Artificial intelligence; Computer science; Pattern recognition (psychology); Inference; Euclidean distance; Fuzzy logic; Image (mathematics); Computer vision; Machine learning; Data mining","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":[0.002999089,0.0004657617,0.0004397836,0.001660662,0.0002084215,0.0009190338,0.0004231419,0.0006798147,0.0009170395],"category_scores_gemma":[0.01294424,0.0001708426,0.0004040314,0.0005286338,0.0006255315,0.001377331,0.000945696,0.0004434572,0.0001771612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005943264,"about_ca_system_score_gemma":0.0002841441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009285932,"about_ca_topic_score_gemma":0.001340883,"domain_scores_codex":[0.9980893,0.0005871513,0.0001938279,0.0004103453,0.0006391563,0.00008018823],"domain_scores_gemma":[0.9942223,0.002674038,0.001138004,0.000389345,0.001359717,0.0002165606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001896494,0.0007272722,0.0694508,0.0005323695,0.00038988,0.0004084544,0.001135356,0.1348706,0.07009102,0.007358767,0.00197945,0.7111596],"study_design_scores_gemma":[0.000036598,0.0007724151,0.0355083,0.00004618913,0.00008037455,0.0002161286,0.0002515491,0.939294,0.01715262,0.005913706,0.000675569,0.00005258178],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.480698,0.0002854365,0.5156523,0.0001442041,0.00003717491,0.0001621074,0.0001440241,0.0002681834,0.002608508],"genre_scores_gemma":[0.9604483,0.00006373847,0.03874043,0.00002825784,0.00002266676,0.0000464313,0.0001489345,0.00001667192,0.0004845798],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002999089,"threshold_uncertainty_score":0.01586086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01890846035430609,"score_gpt":0.2698948960763391,"score_spread":0.250986435722033,"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."}}