{"id":"W3216760285","doi":"10.18280/ts.380507","title":"Diagnosis of Melanoma Lesion Using Neutrosophic and Deep Learning","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Deep learning; Artificial intelligence; Computer science; Melanoma; Skin lesion; Segmentation; Skin cancer; Pattern recognition (psychology); Medicine; Cancer; Dermatology; Cancer research","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003220104,0.0003645922,0.000350882,0.0008280507,0.0001835028,0.0005755764,0.0004256837,0.0006504944,0.000841535],"category_scores_gemma":[0.0006755209,0.0001669935,0.0004392038,0.000298466,0.0002016628,0.0004941169,0.0004084957,0.000458291,0.000225928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004257829,"about_ca_system_score_gemma":0.0002775473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002448596,"about_ca_topic_score_gemma":0.003164305,"domain_scores_codex":[0.9998197,0.0000303371,0.00001581277,0.00005011927,0.00005475581,0.0000293269],"domain_scores_gemma":[0.9998515,0.00004365125,0.0000226093,0.00001274396,0.00005439432,0.00001511783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001125405,0.0003026425,0.01421985,0.0003309552,0.0001401627,0.001085638,0.0002162223,0.2349805,0.09003662,0.005045285,0.004068639,0.6484481],"study_design_scores_gemma":[0.000007315067,0.00008025755,0.002072189,0.00001815902,0.00001286356,0.0001823121,0.00005338535,0.9839994,0.01103833,0.001880156,0.0006453249,0.00001024632],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3256065,0.001135126,0.6668488,0.0005911601,0.00009067109,0.0001659184,0.0004159387,0.0007272434,0.004418668],"genre_scores_gemma":[0.8625741,0.0004036363,0.1347521,0.0001480507,0.00003107091,0.00004461313,0.0004669167,0.00001831373,0.001561348],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002448596,"threshold_uncertainty_score":0.004868746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02986255963706404,"score_gpt":0.262766319870454,"score_spread":0.23290376023339,"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."}}