{"id":"W2550512372","doi":"10.4155/bio-2016-4988","title":"2016 White Paper on Recent Issues in Bioanalysis: Focus on Biomarker Assay Validation (BAV): (Part 2 – Hybrid LBA/LCMS and Input from Regulatory Agencies)","year":2016,"lang":"en","type":"article","venue":"Bioanalysis","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada; Caprion (Canada)","funders":"Agenzia Italiana del Farmaco, Ministero della Salute; Health Canada; World Health Organization; Bristol-Myers Squibb; U.S. Food and Drug Administration; Sanofi; Angelini Pharma","keywords":"Bioanalysis; Biopharmaceutical; Immunogenicity; Excellence; White paper; Biosimilar; Computer science; Nanotechnology; Medicine; Political science; Biotechnology; Biology","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":[0.00162975,0.0004925755,0.0009132929,0.0007428457,0.0001742887,0.0000611314,0.0003424585,0.0004946475,0.005945827],"category_scores_gemma":[0.0004796433,0.0003023413,0.0003783684,0.000823674,0.0004752699,0.0001817132,0.0001434031,0.0002593388,0.000524933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002284016,"about_ca_system_score_gemma":0.00005983436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003141738,"about_ca_topic_score_gemma":0.0002288229,"domain_scores_codex":[0.9958097,0.001373398,0.0008676614,0.001142516,0.0002087749,0.0005979232],"domain_scores_gemma":[0.9977635,0.0006534869,0.0003242706,0.001005081,0.0001426993,0.0001110144],"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":[0.001002641,0.0007162992,0.02966942,0.00001764605,0.004949853,0.00004482866,0.0001642901,0.000004349535,0.1790925,0.000669938,0.03564468,0.7480236],"study_design_scores_gemma":[0.003187628,0.0005099248,0.06346767,0.0004623504,0.002270626,0.000008120935,0.0002922238,0.00008588841,0.2979816,0.002883639,0.6274847,0.001365584],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7371103,0.1003511,0.002598983,0.1314369,0.003621989,0.001799651,0.002621803,0.0006524562,0.01980688],"genre_scores_gemma":[0.9759498,0.009652526,0.0006907316,0.001455809,0.0001415226,0.00004034568,0.0001632796,0.00004566376,0.01186028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.746658,"threshold_uncertainty_score":0.9999429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02645662342934067,"score_gpt":0.2739332351796624,"score_spread":0.2474766117503217,"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."}}