{"id":"W3180432673","doi":"10.1158/1078-0432.ccr-21-2052","title":"Immune Profiling Mass Cytometry Assay Harmonization: Multicenter Experience from CIMAC-CIDC","year":2021,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity","funders":"National Cancer Institute","keywords":"Mass cytometry; Immune system; Flow cytometry; Harmonization; Profiling (computer programming); Medicine; Immunology; Biology; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1237659,0.00175027,0.001287541,0.001934543,0.001807829,0.003233511,0.005293366,0.002026772,0.002557553],"category_scores_gemma":[0.05605925,0.000645092,0.00109512,0.002214249,0.002484223,0.001322479,0.005085807,0.002373183,0.001481524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003280469,"about_ca_system_score_gemma":0.005949476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004490328,"about_ca_topic_score_gemma":0.001953312,"domain_scores_codex":[0.932092,0.03558581,0.003656915,0.01086448,0.0151702,0.002630688],"domain_scores_gemma":[0.9372243,0.01009723,0.005386672,0.01879404,0.02413362,0.004364193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01627883,0.0111662,0.3116877,0.001471658,0.002418172,0.001090958,0.008586265,0.02229072,0.09676454,0.00504314,0.04078594,0.4824159],"study_design_scores_gemma":[0.003546995,0.03803618,0.6241109,0.0009284695,0.001481652,0.00365598,0.002726582,0.02506472,0.1484829,0.0021358,0.1494221,0.0004077483],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8499719,0.008755079,0.108029,0.003936364,0.0006600458,0.007634234,0.004207812,0.002259035,0.01454648],"genre_scores_gemma":[0.8957518,0.001517043,0.08029786,0.00249908,0.0006730989,0.003610409,0.01226541,0.001084945,0.002300439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1237659,"threshold_uncertainty_score":0.6545444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1634933270471794,"score_gpt":0.4655308214199056,"score_spread":0.3020374943727263,"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."}}