{"id":"W1988216288","doi":"10.1016/j.jaad.2011.09.005","title":"Acne severity grading: Determining essential clinical components and features using a Delphi consensus","year":2011,"lang":"en","type":"article","venue":"Journal of the American Academy of Dermatology","topic":"Acne and Rosacea Treatments and Effects","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor; Western University","funders":"","keywords":"Acne; Medicine; Grading (engineering); Delphi method; Categorization; Grading scale; Delphi; Medical physics; Dermatology; Surgery; Artificial intelligence; Computer science","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":[0.0674466,0.0008610422,0.00113444,0.004567202,0.002281671,0.00146483,0.001655662,0.001301702,0.004452009],"category_scores_gemma":[0.04931239,0.0007111714,0.002086478,0.001604893,0.001535306,0.002060276,0.005920306,0.001863097,0.001270325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003547488,"about_ca_system_score_gemma":0.009640583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002059859,"about_ca_topic_score_gemma":0.003789691,"domain_scores_codex":[0.9570522,0.0244517,0.00931358,0.001304648,0.005530708,0.0023471],"domain_scores_gemma":[0.9614685,0.01204634,0.002084523,0.001584481,0.02110194,0.001714194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.003273279,0.00167552,0.1390977,0.007276385,0.0008277397,0.00135203,0.1082237,0.002859939,0.03704676,0.01770307,0.0518171,0.6288468],"study_design_scores_gemma":[0.002422879,0.004702272,0.3327319,0.01309961,0.00190044,0.01119231,0.2063799,0.04448928,0.02739509,0.0478261,0.3063062,0.001554004],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6924099,0.002905925,0.1365936,0.01487228,0.0009927439,0.06034495,0.001870184,0.0004135851,0.08959676],"genre_scores_gemma":[0.7195519,0.001570239,0.2404361,0.001965234,0.0001774056,0.02948389,0.001337583,0.0001346437,0.005343054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0674466,"threshold_uncertainty_score":0.356696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08468723462818897,"score_gpt":0.3836153987262778,"score_spread":0.2989281640980889,"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."}}