{"id":"W4413180314","doi":"10.18280/ts.420413","title":"Modelling a Deep Network Model for Diabetic Foot Ulcer Prediction Using Learning Approaches","year":2025,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Diabetic Foot Ulcer Assessment and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diabetic foot; Artificial intelligence; Diabetic foot ulcer; Computer science; Foot (prosody); Machine learning; Deep learning; Medicine; Diabetes mellitus","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":[0.0004958516,0.0007553261,0.0006104789,0.0005050758,0.0002690928,0.0007840631,0.0009332724,0.001176648,0.002200885],"category_scores_gemma":[0.001412272,0.000390985,0.0006057994,0.0004287466,0.0003082922,0.0005152618,0.000527266,0.001219146,0.0003351916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008127,"about_ca_system_score_gemma":0.0009172331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03140992,"about_ca_topic_score_gemma":0.02213059,"domain_scores_codex":[0.9998435,0.0000274461,0.000009636535,0.00004883286,0.00002584782,0.0000447364],"domain_scores_gemma":[0.9996235,0.0001919699,0.00004004192,0.000009528884,0.0001142173,0.00002070524],"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":[0.00006957162,0.00005989755,0.002390576,0.00003384202,0.00003154044,0.00007493065,0.00001892797,0.972994,0.0005782486,0.001179294,0.0008368559,0.02173238],"study_design_scores_gemma":[0.000001401272,0.000004446868,0.00009673727,0.000002248947,0.000002566975,0.000002600835,0.000001465362,0.9995542,0.00004471873,0.0002429649,0.00004538635,0.000001244615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2729026,0.003886305,0.7083935,0.001762283,0.0003601452,0.0001088551,0.001041369,0.00122533,0.01031958],"genre_scores_gemma":[0.9728061,0.0005478354,0.0201293,0.0002074476,0.00006003426,0.0001280609,0.0005987413,0.00002461126,0.005497953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03140992,"threshold_uncertainty_score":0.06245416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06694546810968514,"score_gpt":0.2753762345822673,"score_spread":0.2084307664725822,"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."}}