{"id":"W4407257800","doi":"10.1007/978-3-031-80871-5_10","title":"Diabetic Foot Ulcer Grand Challenge 2024: Overview and Baseline Methods","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Diabetic Foot Ulcer Assessment and Management","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Baseline (sea); Computer science; Foot (prosody); Diabetic foot; Diabetic foot ulcer; Artificial intelligence; Medicine; Diabetes mellitus; Art; Geology","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":[0.03163245,0.001821723,0.001724876,0.002786918,0.0009515224,0.004053614,0.003813548,0.002336515,0.03080639],"category_scores_gemma":[0.0349637,0.001026911,0.001774109,0.002594648,0.0005614432,0.002353511,0.003279735,0.002945981,0.01817662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002205862,"about_ca_system_score_gemma":0.00653241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01065801,"about_ca_topic_score_gemma":0.01306028,"domain_scores_codex":[0.9893417,0.004828133,0.0007647172,0.0009878203,0.003609932,0.0004675951],"domain_scores_gemma":[0.9873061,0.003543393,0.0006199205,0.001135129,0.006596999,0.0007985198],"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":[0.001336366,0.0004997547,0.004889037,0.001533169,0.0002501293,0.00005016579,0.0001048455,0.001345507,0.0008965618,0.006199976,0.2350377,0.7478568],"study_design_scores_gemma":[0.0009854955,0.002006064,0.03708653,0.005203594,0.0008330449,0.0011749,0.000547184,0.01544316,0.004462646,0.03701205,0.8949521,0.0002932862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01497715,0.1717668,0.5463239,0.02964655,0.01352799,0.00999179,0.07497563,0.007612311,0.1311779],"genre_scores_gemma":[0.04540166,0.05937404,0.6892676,0.01011545,0.005701833,0.01341148,0.08067735,0.003751786,0.09229883],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03163245,"threshold_uncertainty_score":0.1672904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03191396255275639,"score_gpt":0.3363230644054232,"score_spread":0.3044091018526668,"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."}}