{"id":"W3033951167","doi":"10.1109/crv50864.2020.00022","title":"Histological Image Classification using Deep Features and Transfer Learning","year":2020,"lang":"en","type":"article","venue":"","topic":"AI in cancer detection","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Convolutional neural network; Transfer of learning; Artificial intelligence; Support vector machine; Pattern recognition (psychology); Deep learning; Block (permutation group theory); Feature (linguistics); Feature extraction; Contextual image classification; Feature vector; Machine learning; Domain (mathematical analysis); Class (philosophy); Image (mathematics); Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.00005806434,0.00005785382,0.00006470961,0.00002016591,0.0001016827,0.00008205981,0.0001382421,0.0000460514,0.00002168186],"category_scores_gemma":[0.00002512465,0.00004969233,0.00001855317,0.0001456546,0.00003644325,0.0002875552,0.00003877231,0.0001478001,0.00000730608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003815609,"about_ca_system_score_gemma":0.00001258689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001106935,"about_ca_topic_score_gemma":0.00000294889,"domain_scores_codex":[0.9994407,0.00004512487,0.0000767871,0.0002488409,0.00009563186,0.00009297246],"domain_scores_gemma":[0.9998007,0.00002688453,0.00001422933,0.00007840757,0.00002308211,0.00005669348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004380181,0.00002644985,0.002020138,0.00004827404,0.00002046236,0.00001937065,0.004817378,0.001515219,0.660509,0.04609002,0.000707165,0.2841827],"study_design_scores_gemma":[0.000189224,0.0001205,0.01124274,0.000003178711,0.000006940704,0.00004602217,0.0001264283,0.975579,0.009717752,0.0004260607,0.002396584,0.0001456189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04541029,0.0001217579,0.9491284,0.00313974,0.00006343384,0.0000509106,5.801403e-8,0.0002031489,0.001882218],"genre_scores_gemma":[0.9280171,0.00001237157,0.07138829,0.000494216,0.00004623232,0.000002231695,2.614369e-7,0.000003521887,0.00003572055],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9740638,"threshold_uncertainty_score":0.2026395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04908896243934385,"score_gpt":0.2665864291321732,"score_spread":0.2174974666928293,"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."}}