{"id":"W4313383581","doi":"10.4049/jimmunol.200.supp.120.37","title":"Multicolor Immunophenotyping using Flow Cytometry: Evaluation of Multiple Methods for Instrument Optimization","year":2018,"lang":"en","type":"article","venue":"The Journal of Immunology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thermo Fisher Scientific (Canada)","funders":"","keywords":"SIGNAL (programming language); Voltage; Fluorescence; Flow cytometry; Cytometry; Detector; Physics; Optoelectronics; Optics; Computer science; Biology","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":[0.02050408,0.001973768,0.001440029,0.002235985,0.0006604717,0.00196557,0.001374659,0.0009437996,0.001229906],"category_scores_gemma":[0.02226824,0.0006232446,0.001061727,0.001562941,0.0005451927,0.001630711,0.001649712,0.001120668,0.0004618497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001206505,"about_ca_system_score_gemma":0.001062156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008263801,"about_ca_topic_score_gemma":0.0009294638,"domain_scores_codex":[0.989328,0.004702077,0.0007851502,0.001134422,0.003776851,0.0002735756],"domain_scores_gemma":[0.9789068,0.0135121,0.001772551,0.001726339,0.003767936,0.000314206],"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":[0.003175357,0.001607325,0.03136355,0.001739312,0.001025399,0.0001882658,0.0003852161,0.06132438,0.271189,0.004384693,0.002366476,0.6212511],"study_design_scores_gemma":[0.0001787686,0.003201141,0.02522206,0.0002836265,0.001167192,0.0008089483,0.0002527924,0.4431263,0.510165,0.002393553,0.01291183,0.0002887877],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2164782,0.008989371,0.7686038,0.00044699,0.0002305038,0.001390092,0.0003249822,0.001762075,0.001774043],"genre_scores_gemma":[0.2252447,0.002031619,0.7691013,0.0001390459,0.00007532319,0.001294258,0.0003551376,0.000504562,0.001254214],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02050408,"threshold_uncertainty_score":0.1084372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06469427754687551,"score_gpt":0.352742219099429,"score_spread":0.2880479415525535,"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."}}