{"id":"W2896616857","doi":"10.1016/b978-1-4832-2951-5.50049-6","title":"ERYTHEMA MULTIFORME (IRIS)","year":2013,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Autoimmune and Inflammatory Disorders Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut d'Histoire de l'Amérique Française","funders":"","keywords":"Erythema multiforme; IRIS (biosensor); Dermatology; Medicine; Computer science; Artificial intelligence","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":[0.0001393986,0.0005809416,0.0003502719,0.001242445,0.0003745613,0.001155168,0.0002841756,0.0007300396,0.0449643],"category_scores_gemma":[0.0002507018,0.0001432263,0.0002104145,0.0007313894,0.0003855095,0.001174531,0.0006700394,0.001302674,0.01662552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004116661,"about_ca_system_score_gemma":0.0002958104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001323837,"about_ca_topic_score_gemma":0.003524142,"domain_scores_codex":[0.9999037,0.00001564296,0.000006189845,0.00001683383,0.00004458283,0.00001309059],"domain_scores_gemma":[0.9999461,0.00002417094,0.000006003017,0.000004464328,0.00001150375,0.000007688329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004290059,0.00006542233,0.0002569153,0.0004675227,0.000007256202,0.001265493,0.0002038106,0.0001654408,0.003531704,0.0281012,0.261207,0.7046854],"study_design_scores_gemma":[0.000005968479,0.00001703451,0.0004230046,0.0002842279,0.000004712418,0.004186546,0.00006792775,0.00005022205,0.0004845454,0.005144801,0.9893258,0.000005184253],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0024226,0.1978431,0.003009968,0.003633662,0.003573762,0.00005733771,0.0002199302,0.0002789085,0.7889608],"genre_scores_gemma":[0.009377477,0.08670037,0.002762116,0.002567666,0.001643025,0.00003979655,0.0001920377,0.00007990129,0.8966376],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.0449643,"threshold_uncertainty_score":0.1504206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0235208213000032,"score_gpt":0.2744613779281262,"score_spread":0.250940556628123,"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."}}