{"id":"W4415039941","doi":"10.1136/bmjhci-2024-101418","title":"Machine learning model to classify chronic leg wounds and identify pyoderma gangrenosum","year":2025,"lang":"en","type":"article","venue":"BMJ Health & Care Informatics","topic":"Wound Healing and Treatments","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute","funders":"Bundesministerium für Bildung und Forschung","keywords":"Pyoderma gangrenosum; Leg ulcer; Foot (prosody); Wound care; Clinical Practice; Chronic wound","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":[0.0003079128,0.0002177691,0.0004597411,0.0002868098,0.0004009801,0.00007230015,0.00008011555,0.0001386547,0.000009407497],"category_scores_gemma":[0.00009344826,0.0001926278,0.00006521867,0.0002739238,0.0000377426,0.0001337872,0.00009941107,0.0004601853,0.00005792051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009236458,"about_ca_system_score_gemma":0.001575446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002885241,"about_ca_topic_score_gemma":0.000284633,"domain_scores_codex":[0.9982089,0.00003396055,0.0007961805,0.0001499954,0.0003181417,0.000492826],"domain_scores_gemma":[0.9989166,0.00005709454,0.0001826493,0.0003286314,0.0001633476,0.0003516479],"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":[0.0008898688,0.0004326338,0.1258005,0.04447328,0.0008399049,0.0001009282,0.1144711,0.01643597,0.00004160538,0.007187447,0.06892189,0.6204048],"study_design_scores_gemma":[0.01347579,0.003237658,0.04013321,0.006593969,0.0005415407,0.000335101,0.01598066,0.6601994,0.0001559702,0.000620174,0.2577187,0.001007787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8148028,0.02598939,0.03791149,0.04742419,0.001742529,0.00748881,0.0002079665,0.001082073,0.0633508],"genre_scores_gemma":[0.9747567,0.0006963601,0.009584113,0.01084758,0.0001182549,0.00009077752,0.0002646331,0.00002901453,0.003612523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6437634,"threshold_uncertainty_score":0.7855132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03100917085358471,"score_gpt":0.4048254585606502,"score_spread":0.3738162877070654,"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."}}