{"id":"W2905983871","doi":"10.1002/cyto.a.23664","title":"Implementation and Validation of an Automated Flow Cytometry Analysis Pipeline for Human Immune Profiling","year":2018,"lang":"en","type":"article","venue":"Cytometry Part A","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Terry Fox Research Institute; BC Cancer Agency","funders":"","keywords":"Workflow; Computer science; Profiling (computer programming); Cytometry; Pipeline (software); Data mining; Flow cytometry; Database; Immunology; Medicine; 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":[0.000358196,0.0001252583,0.0002174073,0.0002881586,0.0001267223,0.00002851348,0.00009972002,0.000110261,0.00003120917],"category_scores_gemma":[0.00003692367,0.0001267776,0.0001017839,0.0006013288,0.00008133328,0.00001136286,0.00002950505,0.00003333994,9.532707e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001066255,"about_ca_system_score_gemma":0.00002354732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003303037,"about_ca_topic_score_gemma":0.00005383852,"domain_scores_codex":[0.9990214,0.00004439524,0.0003536657,0.0002990478,0.0001053066,0.000176201],"domain_scores_gemma":[0.9993197,0.0000116911,0.0001415111,0.0002483515,0.0002201033,0.00005864419],"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":[0.00008837764,0.00007715224,0.02651062,0.00003868589,0.0002043105,1.716843e-7,0.00006443897,0.00004380362,0.9705373,0.00001112827,0.00005234356,0.002371665],"study_design_scores_gemma":[0.0009024346,0.0005358251,0.006780297,0.000005618312,0.0002703056,0.000001447052,0.000159524,0.01559652,0.9752545,0.00002078677,0.0003244652,0.0001482664],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9358617,0.00009492027,0.06349728,0.000009043571,0.00009322296,0.0002446384,0.000112109,0.00003844288,0.00004861208],"genre_scores_gemma":[0.9905931,0.00001262943,0.006485665,0.00002926553,0.0002643588,0.00002179222,0.002523971,0.00001889585,0.00005036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05701161,"threshold_uncertainty_score":0.5169839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02431908443914182,"score_gpt":0.3464433062092037,"score_spread":0.3221242217700619,"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."}}