{"id":"W4281568012","doi":"10.1155/2022/2415726","title":"Dermoscopic Image Classification Using Deep Belief Learning Network Architecture","year":2022,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"King Saud University","keywords":"Computer science; Artificial intelligence; Overfitting; Pattern recognition (psychology); Preprocessor; Image (mathematics); Segmentation; Network architecture; Contextual image classification; Deep learning; Filter (signal processing); Computer vision; Artificial neural network","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":[0.000374952,0.0005318814,0.0003509386,0.0005003189,0.0001979438,0.0006394208,0.0007370152,0.0007356261,0.001104665],"category_scores_gemma":[0.0008593444,0.0002777152,0.0003557281,0.0003413202,0.0002439728,0.0006462036,0.0004835682,0.0007999227,0.0004079854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000861276,"about_ca_system_score_gemma":0.0005630562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007723195,"about_ca_topic_score_gemma":0.009368229,"domain_scores_codex":[0.9998347,0.00002804312,0.000007645528,0.00004620673,0.00004814317,0.00003526272],"domain_scores_gemma":[0.9997914,0.00006201288,0.0000239232,0.00001705268,0.00009152463,0.00001396898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002685684,0.0002058481,0.004162644,0.0001212704,0.000098832,0.0001622984,0.00006967334,0.5568045,0.02212254,0.003008138,0.002844392,0.4101312],"study_design_scores_gemma":[0.000002131389,0.00002209636,0.0002609002,0.000004127197,0.000006433469,0.00001346668,0.00000389299,0.997378,0.001635726,0.0004413332,0.000229212,0.000002761804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1153073,0.001615666,0.8755202,0.0008312777,0.0001379175,0.00008144882,0.0001580022,0.00205018,0.004297985],"genre_scores_gemma":[0.8883519,0.0006543542,0.1040214,0.0002888075,0.00005385746,0.0000723187,0.0003013759,0.00004553112,0.006210356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007723195,"threshold_uncertainty_score":0.01535648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02294552154698818,"score_gpt":0.2855819185251294,"score_spread":0.2626363969781412,"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."}}