{"id":"W2774120458","doi":"10.4155/bio-2017-4974","title":"2017 White Paper on Recent Issues in Bioanalysis: A Global Perspective on Immunogenicity Guidelines & Biomarker Assay Performance (Part 3 – Lba: Immunogenicity, Biomarkers and PK Assays)","year":2017,"lang":"en","type":"article","venue":"Bioanalysis","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Caprion (Canada); Health Canada; inVentiv Health Clinical","funders":"Health Canada; Genentech; Agence Nationale de Sécurité du Médicament et des Produits de Santé; Angelini Pharma; Sanofi; U.S. Food and Drug Administration; Bristol-Myers Squibb; Ministry of Health, Labour and Welfare; Pfizer; Amgen","keywords":"Bioanalysis; Immunogenicity; Biopharmaceutical; Excellence; Regulatory science; Biosimilar; Computer science; Nanotechnology; Chemistry; Political science; Medicine; Biotechnology; Biology; Chromatography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003486048,0.0008677431,0.001495937,0.0006041084,0.001188758,0.0003276545,0.001272747,0.000894675,0.001671878],"category_scores_gemma":[0.00198855,0.0006697043,0.0007999687,0.0009735198,0.001335735,0.0003598947,0.0006073808,0.0005989614,0.000375314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006756767,"about_ca_system_score_gemma":0.0001209812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003807638,"about_ca_topic_score_gemma":0.003429205,"domain_scores_codex":[0.9945431,0.001137122,0.001306364,0.001631567,0.0003321081,0.001049722],"domain_scores_gemma":[0.995639,0.0002582426,0.0008139328,0.002421442,0.0007195714,0.0001477578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009462532,0.003412316,0.5345663,0.0001347717,0.04078197,0.0001225454,0.0006001769,0.00005552544,0.05739892,0.002619721,0.05382958,0.2970156],"study_design_scores_gemma":[0.005241219,0.0007792802,0.6054751,0.0005262241,0.004081029,0.00008174621,0.001323552,0.0006104689,0.008158847,0.0006662992,0.3707253,0.002330907],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6645098,0.1691654,0.000276746,0.09892301,0.003584051,0.00187799,0.001669572,0.0004197962,0.05957366],"genre_scores_gemma":[0.9606473,0.02936316,0.002107054,0.001874311,0.0001508734,0.00006113277,0.0001377713,0.00005383306,0.005604606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3168957,"threshold_uncertainty_score":0.9995754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08757148376182888,"score_gpt":0.3844078216666881,"score_spread":0.2968363379048592,"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."}}