{"id":"W4406831076","doi":"10.1002/eng2.70001","title":"Multi‐Wound Classification: Exploring Image Enhancement and Deep Learning Techniques","year":2025,"lang":"en","type":"article","venue":"Engineering Reports","topic":"Diabetic Foot Ulcer Assessment and Management","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Artificial intelligence; Deep learning; Computer science; Image (mathematics); Pattern recognition (psychology); Computer vision","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002417482,0.0001206945,0.000166143,0.0001622884,0.00004823066,0.00004433353,0.00002547892,0.00003212632,0.00002891782],"category_scores_gemma":[0.00008813226,0.000121702,0.00003329026,0.0001398623,0.00001719941,0.0001056853,0.0000642168,0.0001399042,0.000002158161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008091435,"about_ca_system_score_gemma":0.00001708224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006390205,"about_ca_topic_score_gemma":4.697798e-7,"domain_scores_codex":[0.9991897,0.000003943178,0.0002553706,0.0002505413,0.0001337121,0.0001667225],"domain_scores_gemma":[0.9996113,0.00001938697,0.00005432137,0.0002191389,0.00004212049,0.0000537616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003050721,0.0004432165,0.05693842,0.002205009,0.0005865492,0.001049218,0.0007806425,0.0001480145,0.6865129,0.002370226,0.0007610584,0.2481743],"study_design_scores_gemma":[0.0008945654,0.0002692988,0.4371438,0.001240041,0.0003866361,0.0001101564,0.0006578947,0.01528739,0.2424365,0.00007939315,0.3008901,0.0006041877],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6800566,0.001204827,0.2956914,0.0009608224,0.0009712899,0.001137574,1.480358e-7,0.001008242,0.01896912],"genre_scores_gemma":[0.9409631,0.0002131397,0.05502638,0.00004070672,0.00005198188,0.0002597745,0.00000950194,0.00001718689,0.003418216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4440764,"threshold_uncertainty_score":0.4962864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0201937675069146,"score_gpt":0.2811322713924951,"score_spread":0.2609385038855805,"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."}}