{"id":"W2065920170","doi":"10.1109/embc.2012.6345881","title":"Illumination correction in dermatological photographs using multi-stage illumination modeling for skin lesion analysis","year":2012,"lang":"en","type":"article","venue":"","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Artificial intelligence; Parametric statistics; Segmentation; Computer science; Parametric model; Monte Carlo method; Computer vision; Pixel; Sampling (signal processing); Pattern recognition (psychology); Mathematics; Statistics","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":[0.0008918088,0.0006492984,0.0006504919,0.0008934772,0.000324872,0.001039164,0.0009470238,0.0007700212,0.001148469],"category_scores_gemma":[0.002008339,0.000484362,0.001074524,0.0006021667,0.0003586444,0.0008200399,0.0006725348,0.0008709515,0.0005964959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000592973,"about_ca_system_score_gemma":0.0007291193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001987971,"about_ca_topic_score_gemma":0.004257839,"domain_scores_codex":[0.9993438,0.0001169537,0.00003677951,0.0001642866,0.0002877128,0.00005045953],"domain_scores_gemma":[0.9989924,0.0003087124,0.0001695893,0.0002774245,0.0002244136,0.00002753043],"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":[0.0002958991,0.0001222758,0.003426789,0.0002308572,0.0001371701,0.0001758396,0.000240499,0.1249138,0.2466083,0.002569948,0.001437346,0.6198413],"study_design_scores_gemma":[0.00001278595,0.0001102643,0.004766718,0.00001490328,0.00005512792,0.0006676115,0.00003640163,0.8873993,0.1027919,0.001250744,0.002842327,0.00005199029],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01230688,0.00009051043,0.9865086,0.00003303406,0.00001020716,0.0000288981,0.00002115087,0.0008181648,0.00018257],"genre_scores_gemma":[0.1410305,0.0002027232,0.8573321,0.00003644992,0.0000148174,0.00005591895,0.0001327136,0.000192234,0.001002556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001987971,"threshold_uncertainty_score":0.004716396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08581987626526684,"score_gpt":0.3264846388200694,"score_spread":0.2406647625548026,"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."}}