{"id":"W2791278436","doi":"10.1097/der.0000000000000342","title":"Rubber Accelerators in Medical Examination and Surgical Gloves","year":2018,"lang":"en","type":"article","venue":"Dermatitis","topic":"Contact Dermatitis and Allergies","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Surgical Gloves; Medicine; Product (mathematics); Product line; Medical emergency; Surgery; Medical physics; Manufacturing engineering; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001497161,0.00008870098,0.0001893929,0.0001037349,0.0000422689,0.00003453945,0.00004329217,0.00009324649,0.001695909],"category_scores_gemma":[0.00009439905,0.00007551593,0.00002415158,0.0001343649,0.0001158103,0.0001555724,0.00004169144,0.0001097099,0.00007096676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002426447,"about_ca_system_score_gemma":0.00004343437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007836642,"about_ca_topic_score_gemma":0.0002806489,"domain_scores_codex":[0.9991465,0.00004617837,0.0002269914,0.0001336424,0.0002914877,0.0001551814],"domain_scores_gemma":[0.9996174,0.00006951488,0.00003017045,0.0001044617,0.00005064235,0.0001278113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0000197238,0.0002523637,0.4489491,0.000246191,0.00006541635,0.003799338,0.004198592,1.097494e-7,0.0001853215,0.00570467,0.03160862,0.5049706],"study_design_scores_gemma":[0.001334719,0.00006683973,0.9123443,0.0001652722,0.00000655201,0.001167359,0.0001206091,0.0006658929,0.0006696556,0.00008741733,0.08328161,0.00008978185],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9636915,0.0003097467,0.00002327787,0.004942343,0.0001133722,0.0001163942,0.000002797383,0.00003714124,0.03076341],"genre_scores_gemma":[0.9966901,0.0004032133,0.0001080338,0.002290958,0.0002159243,0.000009935051,0.00001444476,0.000008970381,0.0002584231],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5048808,"threshold_uncertainty_score":0.9992167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0129196366165149,"score_gpt":0.2740662901394587,"score_spread":0.2611466535229438,"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."}}