{"id":"W2290269515","doi":"10.1038/srep20686","title":"Standardizing Flow Cytometry Immunophenotyping Analysis from the Human ImmunoPhenotyping Consortium","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":289,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity; University of British Columbia; St. Thomas Hospital; BC Cancer Agency","funders":"National Institute of Allergy and Infectious Diseases; National Heart, Lung, and Blood Institute; Cambridge Institute for Medical Research, University of Cambridge; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Wellcome Trust","keywords":"Immunophenotyping; Standardization; Computer science; Identification (biology); Gating; Flow cytometry; Medicine; Biology; Immunology; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.001318117,0.0002161967,0.0002763708,0.0001314144,0.0008881763,0.0003186705,0.0003509871,0.0001316858,0.0001679751],"category_scores_gemma":[0.0002204346,0.0001356213,0.0003471722,0.0006320742,0.0004220993,0.00001539765,0.0001550444,0.0001077902,0.000011388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004860855,"about_ca_system_score_gemma":0.0001296475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001729653,"about_ca_topic_score_gemma":0.0001357232,"domain_scores_codex":[0.997593,0.0001075973,0.0005955327,0.0009049087,0.0003923475,0.0004066043],"domain_scores_gemma":[0.9978426,0.00005023639,0.0002932786,0.001513795,0.0002136107,0.00008655148],"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":[0.00002324869,0.00002819646,0.03375363,0.000003277388,0.0004536111,0.0000188503,0.0001148948,0.00006882013,0.9603255,0.00001571773,0.0009495168,0.004244714],"study_design_scores_gemma":[0.0006160784,0.00005884252,0.02485965,0.00009636921,0.0005605506,0.00002707681,0.000216389,0.0001033976,0.9033875,0.001910824,0.06752955,0.0006337506],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9635128,0.001642067,0.03068735,0.000126714,0.003200088,0.000165802,0.00004068936,0.00003880581,0.0005856471],"genre_scores_gemma":[0.9974258,0.00002595123,0.000826324,0.00008494845,0.0002649609,0.00001118364,0.0002420974,0.00002723727,0.001091498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06658003,"threshold_uncertainty_score":0.6831223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01373654536227796,"score_gpt":0.243848787332761,"score_spread":0.230112241970483,"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."}}