{"id":"W3185054588","doi":"10.21203/rs.3.rs-712718/v1","title":"DUNEScan: A Web Application for Uncertainty Estimation in Skin Cancer Detection with Deep Neural Networks","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université du Québec à Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"Fonds de recherche du Québec – Nature et technologies; Compute Canada","keywords":"Convolutional neural network; Computer science; Upload; Artificial intelligence; Deep learning; Machine learning; Skin cancer; Artificial neural network; Variance (accounting); Software; Skin lesion; Pattern recognition (psychology); Data mining; Cancer; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007723295,0.002015397,0.0008591368,0.003249673,0.0003267356,0.001551063,0.002305366,0.001264391,0.05411798],"category_scores_gemma":[0.004231007,0.0007124277,0.000926632,0.001153113,0.000344246,0.001444303,0.002474057,0.001129286,0.01202969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008895997,"about_ca_system_score_gemma":0.001017469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009116777,"about_ca_topic_score_gemma":0.01508742,"domain_scores_codex":[0.999432,0.0000613376,0.00003509888,0.0001338779,0.0002816083,0.00005595174],"domain_scores_gemma":[0.9987559,0.0007260506,0.00006557925,0.0001264394,0.0002450512,0.00008093988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008941556,0.0002317945,0.004610965,0.001174213,0.0003822606,0.0007240178,0.000164791,0.038164,0.007283987,0.007224431,0.6402636,0.2988818],"study_design_scores_gemma":[0.0003983392,0.00008234795,0.004318042,0.0002240339,0.00006815832,0.0004900725,0.00009124558,0.7870215,0.02318076,0.02468903,0.1592439,0.0001925449],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.01005881,0.0009756912,0.2065686,0.0005946388,0.0002322601,0.000380516,0.03127439,0.7384052,0.0115099],"genre_scores_gemma":[0.2910514,0.001778707,0.4543037,0.001962294,0.0002844236,0.002121683,0.1219338,0.08658665,0.03997731],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.05411798,"threshold_uncertainty_score":0.1810427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02803495577640215,"score_gpt":0.3637758591207445,"score_spread":0.3357409033443424,"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."}}