{"id":"W4303184445","doi":"10.1021/acsmeasuresciau.2c00038","title":"Development of Multiplexed Bead-Based Immunoassays for Profiling Soluble Cytokines and CD163 Using Mass Cytometry","year":2022,"lang":"en","type":"article","venue":"ACS Measurement Science Au","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fluidigm (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multiplex; Mass cytometry; Analyte; Immunoassay; Cytokine; Peripheral blood mononuclear cell; Chromatography; Cytometry; Chemistry; Flow cytometry; Molecular biology; Immunology; Medicine; Biology; Antibody; In vitro; Bioinformatics; Biochemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.001555444,0.0000959379,0.00009640378,0.00008809437,0.0007360211,0.00001568637,0.000231229,0.00002601767,7.023095e-7],"category_scores_gemma":[0.0001438841,0.00009556217,0.00002898002,0.0002931702,0.0001763529,0.000007337153,0.0001704027,0.00004309016,6.975228e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001857504,"about_ca_system_score_gemma":0.0007083485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009389977,"about_ca_topic_score_gemma":0.000006756924,"domain_scores_codex":[0.9987291,0.00001373801,0.0002078168,0.0003227341,0.00048603,0.0002405713],"domain_scores_gemma":[0.9992378,0.000006985881,0.0001357754,0.0002385977,0.0003393929,0.00004141061],"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":[0.00002645467,0.00004116954,0.0006507142,0.00001643048,0.00000634854,6.944297e-8,0.00003041294,0.0004444965,0.9974321,0.00005582818,0.000009579621,0.001286435],"study_design_scores_gemma":[0.0002858325,0.00007934645,0.0002722889,0.00001125425,0.000008056096,0.000001697149,0.0001724664,0.001988233,0.9946411,0.00007305631,0.002340395,0.0001262471],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7902462,0.00008215458,0.2090326,0.00005648185,0.00006753775,0.0004634932,0.00001118869,0.00001634753,0.00002394648],"genre_scores_gemma":[0.6815036,0.000001407422,0.3183517,0.0000379269,0.00001368798,0.00006702161,0.00001249667,0.00000717528,0.000005027181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1093191,"threshold_uncertainty_score":0.5660954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07062369513825908,"score_gpt":0.318341842487774,"score_spread":0.2477181473495149,"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."}}