{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01352346,0.0008615888,0.0006877443,0.001465973,0.001604583,0.002494272,0.002179288,0.001263885,0.003412482],"category_scores_gemma":[0.01133254,0.0006650343,0.0008489443,0.0008064001,0.001029683,0.001076197,0.001403164,0.001844096,0.002325138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001596423,"about_ca_system_score_gemma":0.00575801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004292007,"about_ca_topic_score_gemma":0.004139718,"domain_scores_codex":[0.9929852,0.001517361,0.0006733889,0.001070603,0.003222844,0.0005305277],"domain_scores_gemma":[0.9929229,0.001608304,0.0003444181,0.001393889,0.003437404,0.0002929549],"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":[0.0008318779,0.0009134244,0.009719546,0.0004099121,0.0001125301,0.0002978859,0.000787709,0.01652774,0.7933582,0.006193673,0.01252097,0.1583264],"study_design_scores_gemma":[0.0002014073,0.001236151,0.01155544,0.0001019588,0.00009545362,0.0004343444,0.0001454653,0.1439629,0.7778242,0.002736003,0.061504,0.0002025805],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07858826,0.0002626998,0.8992091,0.0007661966,0.0002889028,0.003777327,0.002532673,0.0115761,0.002998769],"genre_scores_gemma":[0.1141098,0.0002623251,0.8742776,0.0004655199,0.00005597691,0.002993657,0.004750291,0.0008691713,0.002215639],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01352346,"threshold_uncertainty_score":0.07151973,"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."}}