{"id":"W4303444817","doi":"10.1145/3549555.3549584","title":"Skin Cancer Detection using Ensemble Learning and Grouping of Deep Models","year":2022,"lang":"en","type":"article","venue":"","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"New Brunswick Innovation Foundation; Compute Canada","keywords":"Pipeline (software); Computer science; Artificial intelligence; Convolutional neural network; Deep learning; Skin cancer; Upsampling; Machine learning; Informatics; Weighting; Contextual image classification; Pattern recognition (psychology); Image (mathematics); Cancer; Medicine; Engineering; Radiology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001006053,0.00004990353,0.0001050552,0.0001073255,0.0001519786,0.000005348607,0.00001355055,0.00001401319,0.0004026331],"category_scores_gemma":[0.000006065502,0.00005043872,0.00002791244,0.0001233486,0.00001049758,0.00003067292,0.00006785472,0.00009736326,3.386114e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009929558,"about_ca_system_score_gemma":0.00000967241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000718764,"about_ca_topic_score_gemma":0.0001902598,"domain_scores_codex":[0.9995225,0.00002735394,0.0001098644,0.0001182206,0.0001339682,0.00008810114],"domain_scores_gemma":[0.9998367,0.00001157789,0.00004810429,0.00005102971,0.00002079734,0.0000317284],"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":[0.0004093196,0.0001035098,0.00215347,0.0002281043,0.0001620678,0.00005232025,0.001690517,0.1431085,0.4317582,0.0005931575,0.00002210519,0.4197187],"study_design_scores_gemma":[0.00066223,0.0002898355,0.000276327,0.00001515992,0.00009421806,0.0003910579,0.003416173,0.9700189,0.02033229,0.0001535117,0.004254341,0.00009600317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9228786,0.0002209422,0.07088969,0.00004795215,0.0001286052,0.0001584345,2.476248e-7,0.00004689602,0.005628603],"genre_scores_gemma":[0.9975564,0.00004161076,0.0006307511,0.00009318512,0.00003080722,0.00001461976,6.76514e-7,0.00001024266,0.001621712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8269103,"threshold_uncertainty_score":0.440855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02196395503072651,"score_gpt":0.2692660485208587,"score_spread":0.2473020934901322,"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."}}