{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02593222,0.001935417,0.001685263,0.002144605,0.002760141,0.01290547,0.005615492,0.02612763,0.05933369],"category_scores_gemma":[0.02050568,0.001304137,0.002357576,0.00169492,0.003393634,0.004815526,0.00413732,0.01156909,0.06898073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00562959,"about_ca_system_score_gemma":0.02291834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008241385,"about_ca_topic_score_gemma":0.01063032,"domain_scores_codex":[0.9788406,0.00273812,0.001564119,0.001722789,0.01283357,0.002300876],"domain_scores_gemma":[0.9714694,0.005883982,0.002932835,0.001407227,0.01451715,0.003789428],"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":[0.00007516139,0.00007522614,0.000112825,0.0002641582,0.000009085421,0.0001679135,0.00005599179,0.0001411362,0.001890779,0.00482602,0.9658991,0.02648266],"study_design_scores_gemma":[0.00001077361,0.0000346468,0.0002226552,0.000199413,0.000005455436,0.00005657884,0.0000296063,0.00005491502,0.0008194884,0.0009403162,0.9976143,0.00001199584],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002802298,0.04601825,0.01424116,0.2615424,0.1842023,0.002415697,0.007903271,0.002666943,0.4782078],"genre_scores_gemma":[0.007682682,0.0146832,0.01130781,0.2011553,0.02972227,0.001041953,0.006058163,0.00183554,0.7265131],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05933369,"threshold_uncertainty_score":0.1984909,"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."}}