{"id":"W3042927633","doi":"10.1097/der.0000000000000584","title":"Identifying Acrylates in Medical Adhesives","year":2020,"lang":"en","type":"article","venue":"Dermatitis","topic":"Surgical Sutures and Adhesives","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Adhesive; Dermatology; Composite material","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":[0.00005018496,0.00007907081,0.0002082896,0.00003521703,0.00002512543,0.0000187434,0.00007392125,0.0000777558,0.002723779],"category_scores_gemma":[0.0003626767,0.00006369683,0.0000769556,0.000173316,0.00004014062,0.00007507075,0.00004336415,0.0001812222,0.0002239944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001088817,"about_ca_system_score_gemma":0.00003237807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002893545,"about_ca_topic_score_gemma":0.00001084478,"domain_scores_codex":[0.9991661,0.00002888481,0.0002036219,0.0001419477,0.0002931697,0.0001663267],"domain_scores_gemma":[0.9995289,0.00009165514,0.00002610688,0.00006970911,0.00001630722,0.0002673175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009895817,0.0003742992,0.7159865,0.001377773,0.0002113362,0.01910079,0.0131303,0.000009431186,0.005494963,0.005498274,0.1104233,0.1282941],"study_design_scores_gemma":[0.001825706,0.00008442827,0.8670775,0.0003971818,0.00002309586,0.0002602069,0.0008330755,0.001383631,0.006355979,0.00043462,0.1211363,0.0001882888],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8955441,0.001731344,0.0001119778,0.09577912,0.0001000175,0.000146525,0.000003517902,0.00008928015,0.00649419],"genre_scores_gemma":[0.972936,0.0003458573,0.0002277425,0.02619554,0.0002076659,0.000006680861,0.00001116141,0.000009633846,0.00005971192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.151091,"threshold_uncertainty_score":0.9981878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02962645220887996,"score_gpt":0.296582759762423,"score_spread":0.2669563075535431,"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."}}