{"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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007614158,0.0001967511,0.0001798577,0.0002766075,0.0003415725,0.001221786,0.001038897,0.00009143338,0.00005342405],"category_scores_gemma":[0.0001952609,0.000195053,0.00008769542,0.0003572865,0.00008254872,0.00315675,0.0001858653,0.0007591691,0.00001821476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000584462,"about_ca_system_score_gemma":0.0001851954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002676727,"about_ca_topic_score_gemma":0.000002270632,"domain_scores_codex":[0.9976621,0.0002857897,0.0004517575,0.0004736434,0.0008182345,0.0003084741],"domain_scores_gemma":[0.9986661,0.00004895742,0.000388583,0.00009240182,0.0006214921,0.0001824608],"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":[0.0001201619,0.00009677827,0.006791954,0.00002208613,0.00001015067,0.0006260207,0.002117373,0.008371547,0.4745497,0.00001705017,0.000005521388,0.5072716],"study_design_scores_gemma":[0.0008187275,0.0001994509,0.006688608,0.00007695928,0.00001035476,0.00159397,0.0003069847,0.9100301,0.07867607,0.001119955,0.0001527713,0.0003261039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2000844,0.0002354764,0.7981098,0.0005490726,0.0003959939,0.00003753186,7.29296e-7,0.0001299282,0.0004569796],"genre_scores_gemma":[0.903913,0.00002292065,0.09493069,0.0003406852,0.0007439913,0.000004224415,0.000001474741,0.00001984341,0.00002314261],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9016585,"threshold_uncertainty_score":0.999815,"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."}}