{"id":"W3086921797","doi":"10.5121/sipij.2020.11401","title":"Melanoma Cell Detection in Lymph Nodes Histopathological Images using Deep Learning","year":2020,"lang":"en","type":"article","venue":"Signal & Image Processing An International Journal","topic":"AI in cancer detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Lymph; Melanoma; Pathology; Deep learning; Medicine; Artificial intelligence; Computer science; Cancer research","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":[0.0001932021,0.0003403958,0.0002316641,0.001013157,0.0001711418,0.0003515906,0.0003265998,0.0004776253,0.0009200677],"category_scores_gemma":[0.0004419844,0.000188242,0.0002726995,0.0003572612,0.0001585899,0.000362815,0.0003450362,0.0002598327,0.000424397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000291601,"about_ca_system_score_gemma":0.0002547605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002587679,"about_ca_topic_score_gemma":0.005026549,"domain_scores_codex":[0.9998897,0.00001538143,0.000006181205,0.00002602516,0.000033955,0.0000286533],"domain_scores_gemma":[0.9998957,0.0000231099,0.00002012984,0.00001209988,0.00003529812,0.00001370236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005034568,0.0002396908,0.02719731,0.0002045432,0.00009412546,0.001201976,0.0001410601,0.03994358,0.3947752,0.001306031,0.00340813,0.5309849],"study_design_scores_gemma":[0.00001996563,0.0001497908,0.01722901,0.00003635881,0.0000444498,0.0008310313,0.00009685665,0.8781754,0.09877458,0.001796804,0.002826334,0.00001940979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5226637,0.001749475,0.4684681,0.0004002077,0.00008042293,0.0001422151,0.0004640319,0.002232093,0.003799704],"genre_scores_gemma":[0.8979158,0.0005483289,0.09803975,0.0001157165,0.00002864019,0.00004211413,0.000370666,0.00003738075,0.002901537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002587679,"threshold_uncertainty_score":0.005145252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02175112502726661,"score_gpt":0.2815049170893481,"score_spread":0.2597537920620814,"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."}}