{"id":"W2079922864","doi":"10.1109/ccece.2010.5575143","title":"Segmentation and analysis of the tissue composition of dermatological ulcers","year":2010,"lang":"en","type":"article","venue":"","topic":"Diagnosis and Treatment of Venous Diseases","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Lesion; Medicine; Segmentation; Image segmentation; Granulation tissue; Dermatology; Computer science; Artificial intelligence; Pathology; Surgery; Wound healing","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":[0.0003667073,0.0001951736,0.0002457502,0.00171485,0.0001943237,0.0005609489,0.0002342725,0.0003852094,0.0004918102],"category_scores_gemma":[0.0006405565,0.0002011407,0.0001974588,0.0004612533,0.0001621399,0.0001500194,0.0001586308,0.0001516313,0.0001854428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001853349,"about_ca_system_score_gemma":0.0002402495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001181043,"about_ca_topic_score_gemma":0.001439506,"domain_scores_codex":[0.9998241,0.0000340234,0.00001367474,0.000037654,0.00005960078,0.00003099207],"domain_scores_gemma":[0.9998024,0.00006552188,0.00001931072,0.00002307892,0.00007157069,0.00001816586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003935882,0.00007278039,0.01452146,0.0001659629,0.00004029193,0.0006701747,0.0002955758,0.005294523,0.7860737,0.0003980838,0.0004021261,0.1916717],"study_design_scores_gemma":[0.00006362377,0.0003951799,0.2414815,0.00007336002,0.0001688479,0.007886833,0.0006248037,0.2764668,0.4650595,0.001396996,0.006320696,0.00006175754],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8519151,0.0007594207,0.1455156,0.0000670635,0.00001807839,0.0001275833,0.0001705443,0.0003139921,0.00111272],"genre_scores_gemma":[0.8670432,0.0003985356,0.1312039,0.00003292343,0.00001598274,0.00004355079,0.0002851374,0.00005691589,0.0009199141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00171485,"threshold_uncertainty_score":0.002348363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0103886480722306,"score_gpt":0.2931266450834459,"score_spread":0.2827379970112153,"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."}}