{"id":"W2185272193","doi":"10.4155/bio.15.226","title":"2015 White Paper on Recent Issues in Bioanalysis: Focus on New Technologies and Biomarkers (Part 3 – Lba, Biomarkers and Immunogenicity)","year":2015,"lang":"en","type":"article","venue":"Bioanalysis","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Health Canada; Genentech; Angelini Pharma; Bundesinstitut für Arzneimittel und Medizinprodukte; Amgen; Pfizer; U.S. Food and Drug Administration; Bristol-Myers Squibb; Eli Lilly and Company; Agence Nationale de Sécurité du Médicament et des Produits de Santé; Biogen","keywords":"Bioanalysis; Biopharmaceutical; Immunogenicity; Computer science; Nanotechnology; Medicine; Biotechnology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01508743,0.001455624,0.001095542,0.002329054,0.002434762,0.00869022,0.002399386,0.008626061,0.02590474],"category_scores_gemma":[0.01581145,0.0007546612,0.001506514,0.001665118,0.002859426,0.005794714,0.003550422,0.007179396,0.01610307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004472372,"about_ca_system_score_gemma":0.01119456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004036607,"about_ca_topic_score_gemma":0.006813509,"domain_scores_codex":[0.9917151,0.0009989523,0.0006847027,0.00107631,0.004731039,0.0007938854],"domain_scores_gemma":[0.9835705,0.003107549,0.00164265,0.0007114544,0.008022382,0.002945465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004047583,0.00005143469,0.0001278102,0.0003097844,0.0000101578,0.00008026591,0.0001542572,0.0001419364,0.001377194,0.007228663,0.9441074,0.04637057],"study_design_scores_gemma":[0.000003144731,0.00002337163,0.0001881637,0.0002204345,0.000004590968,0.00003620694,0.00006240928,0.00004603027,0.0006110842,0.001350555,0.9974459,0.000008112931],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.002316024,0.08608622,0.01235789,0.2772606,0.5225133,0.0005031062,0.001400629,0.0006352479,0.09692693],"genre_scores_gemma":[0.0171237,0.08824015,0.0138372,0.2094216,0.1619977,0.000521903,0.003896688,0.001022344,0.5039387],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02590474,"threshold_uncertainty_score":0.08666003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03360566082740423,"score_gpt":0.2941366264752786,"score_spread":0.2605309656478743,"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."}}