{"id":"W4398210924","doi":"10.1080/17576180.2024.2340961","title":"2023 White Paper on Recent Issues in Bioanalysis: EU IVDR 2017/746 Implementation/Impact, IVD/CDx/CLIA Approved Assays, High Dimensional Cytometry, Multiplexing Technologies, LBA Tissue Analysis, Vaccine Study Endpoints, Cell-Based Assays for Biomarkers, Cell Therapy and Vaccines ( <u>PART 2</u> – Recommendations on Development &amp; Validation of Biomarkers, IVD, CDx, Cell-Based, Flow Cytometry, Ligand-Binding and Enzyme Assays; Advanced Critical Reagents Strategies)","year":2024,"lang":"en","type":"article","venue":"Bioanalysis","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pfizer (Canada)","funders":"U.S. Food and Drug Administration; Ministry of Health, Labour and Welfare; Exelixis; Biogen; Sanofi; Health Canada; Spark Therapeutics; Genentech; AstraZeneca","keywords":"Bioanalysis; Chemistry; Computational biology; 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":[0.00365128,0.001006153,0.001759625,0.004743074,0.0005704454,0.0003269052,0.0004873036,0.0006889977,0.001036841],"category_scores_gemma":[0.0004879575,0.000814378,0.0005294542,0.005792767,0.00020543,0.000356933,0.0002087414,0.0005539884,0.00002063089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004190895,"about_ca_system_score_gemma":0.0002795385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004336789,"about_ca_topic_score_gemma":0.001156991,"domain_scores_codex":[0.9933082,0.001237646,0.002053375,0.001957198,0.000468261,0.0009753275],"domain_scores_gemma":[0.9954118,0.002330343,0.00067701,0.0009441377,0.0004644183,0.0001723527],"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":[0.006751104,0.01045527,0.08394007,0.001036418,0.03206453,0.00007336205,0.0008632705,0.003477116,0.6661041,0.00009390954,0.01488934,0.1802515],"study_design_scores_gemma":[0.01140591,0.002649945,0.01434215,0.0003966754,0.007417385,0.000005083907,0.006149633,0.007003058,0.9182936,0.000127066,0.030188,0.002021486],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8115357,0.06328421,0.07784262,0.02579625,0.002305301,0.009096893,0.008712326,0.001062287,0.0003644695],"genre_scores_gemma":[0.9563236,0.002171598,0.03589271,0.0001731801,0.00004053736,0.0002952415,0.004779354,0.00007630794,0.0002474239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2521895,"threshold_uncertainty_score":0.9998763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03989283854876578,"score_gpt":0.3678123926781478,"score_spread":0.327919554129382,"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."}}