{"id":"W3121304865","doi":"10.4155/bio-2021-0005","title":"2020 White Paper on Recent Issues in Bioanalysis: BAV Guidance, CLSI H62, Biotherapeutics Stability, Parallelism Testing, CyTOF and Regulatory Feedback ( <u>Part 2A</u> –Recommendations on Biotherapeutics Stability, PK LBA Regulated Bioanalysis, Biomarkers Assays, Cytometry Validation &amp; Innovation <u>Part 2B</u> –Regulatory Agencies’ Inputs on Bioanalysis, Biomarkers, Immunogenicity, Gene &amp; Cell Therapy and Vaccine)","year":2021,"lang":"en","type":"article","venue":"Bioanalysis","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Bioanalysis; Excellence; Biosimilar; Biopharmaceutical; Computer science; Regulatory science; Business; Biotechnology; Political science; Nanotechnology; Medicine; Biology","routes":{"ca_aff":true,"ca_fund":false,"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","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.005444953,0.001505632,0.00226345,0.00315996,0.0008990339,0.0004617137,0.000822316,0.001415522,0.003857981],"category_scores_gemma":[0.0008755848,0.001355969,0.0008224561,0.01461264,0.001097441,0.0004503063,0.0004362858,0.0009700955,0.00007534932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009658882,"about_ca_system_score_gemma":0.0003996584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003243502,"about_ca_topic_score_gemma":0.0009725217,"domain_scores_codex":[0.987442,0.003921225,0.003410041,0.00299023,0.0008389618,0.001397537],"domain_scores_gemma":[0.9922484,0.001181675,0.001548602,0.003075047,0.001652702,0.0002935469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002332401,0.004675271,0.2126781,0.0003021962,0.02063136,0.0000233185,0.0008211739,0.0001416785,0.6695895,0.0006334996,0.003643128,0.08452842],"study_design_scores_gemma":[0.008419383,0.001199079,0.1659887,0.0006695653,0.005409475,0.00005107989,0.001814801,0.0009172035,0.4890974,0.0008683227,0.3217435,0.003821543],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8932092,0.07988495,0.0007551166,0.02176921,0.0008381755,0.001299738,0.0008972831,0.00037333,0.0009729558],"genre_scores_gemma":[0.9172692,0.05827099,0.0133639,0.006051102,0.0002360123,0.00009922675,0.003017928,0.0002022764,0.001489313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3181003,"threshold_uncertainty_score":0.9998809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0716324586553338,"score_gpt":0.3108688262131721,"score_spread":0.2392363675578383,"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."}}