{"id":"W4405850224","doi":"10.61822/amcs-2024-0041","title":"Enhancing multi-class prediction of skin lesions with feature importance assessment","year":2024,"lang":"en","type":"article","venue":"International Journal of Applied Mathematics and Computer Science","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"HORIZON EUROPE Framework Programme; European Commission","keywords":"Class (philosophy); Feature (linguistics); Computer science; Artificial intelligence; Pattern recognition (psychology); Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003175936,0.00006496721,0.0001315997,0.0002249985,0.00003406729,0.00008324304,0.0001289291,0.00001780657,0.000008656262],"category_scores_gemma":[0.000004775488,0.00004334897,0.00003408162,0.0001521428,0.00008177327,0.00008415143,0.00005853313,0.0001221148,6.729807e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006856978,"about_ca_system_score_gemma":0.0001358309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.433275e-7,"about_ca_topic_score_gemma":0.000001678126,"domain_scores_codex":[0.9990139,0.000001540897,0.0002494173,0.0001138828,0.0005534343,0.00006780676],"domain_scores_gemma":[0.9994437,0.00003145063,0.0001562289,0.0000762316,0.0002310416,0.00006134412],"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":[0.000385522,0.001971998,0.0006325052,0.001495485,0.00149026,0.001391708,0.008377892,0.002368341,0.3566813,0.2622663,0.002366591,0.3605722],"study_design_scores_gemma":[0.002506213,0.001364231,0.00968515,0.002875695,0.00026998,0.008471224,0.001272648,0.9130301,0.04973773,0.002689182,0.007839737,0.0002580874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2470279,0.0000610972,0.750025,0.0005832374,0.000737468,0.0001441734,0.000004008787,0.00001805287,0.001399036],"genre_scores_gemma":[0.7494907,0.00003911602,0.2501895,0.00007573273,0.0001541585,0.00000172603,6.486174e-7,0.000004570089,0.00004382328],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9106618,"threshold_uncertainty_score":0.176772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0120998460216162,"score_gpt":0.2765519172911395,"score_spread":0.2644520712695234,"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."}}