{"id":"W2301690523","doi":"10.1016/j.yexcr.2016.03.007","title":"Identification of neutrophil surface marker changes in health and inflammation using high-throughput screening flow cytometry","year":2016,"lang":"en","type":"article","venue":"Experimental Cell Research","topic":"Neutrophil, Myeloperoxidase and Oxidative Mechanisms","field":"Immunology and Microbiology","cited_by":187,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Biology; Cluster of differentiation; Flow cytometry; CD16; Innate immune system; Immunology; Cell sorting; Inflammation; Integrin alpha M; Cell; Immune system; CD8; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000578576,0.0003875539,0.000475236,0.0007080444,0.000360186,0.0006774046,0.0003332165,0.0004696005,0.001148911],"category_scores_gemma":[0.0004083206,0.0001428765,0.0003552225,0.000503529,0.0002743843,0.000403539,0.0003807273,0.0006308224,0.0002617358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002773757,"about_ca_system_score_gemma":0.0002351638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004835198,"about_ca_topic_score_gemma":0.0008470002,"domain_scores_codex":[0.999576,0.00008376576,0.00002759753,0.00007132551,0.0001428622,0.00009830348],"domain_scores_gemma":[0.9997937,0.00007778325,0.00003069338,0.0000271119,0.00005020556,0.00002047798],"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":[0.000254586,0.0001201753,0.001847196,0.00004110554,0.00001178556,0.00002492556,0.00004231793,0.000152517,0.991597,0.0001562518,0.0001213818,0.0056306],"study_design_scores_gemma":[0.00003268156,0.000596616,0.03576251,0.000007488445,0.00005963364,0.0001680304,0.00007778389,0.007045486,0.9542571,0.0004764869,0.001496503,0.0000197983],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9388964,0.00122936,0.05562424,0.0001980404,0.000042041,0.0003861811,0.001246994,0.0003812679,0.001995543],"genre_scores_gemma":[0.9587585,0.001093079,0.03494339,0.0002197759,0.00004245276,0.0007306318,0.001303947,0.00003194894,0.002876346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001148911,"threshold_uncertainty_score":0.003843486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05954669223149994,"score_gpt":0.3512936429043038,"score_spread":0.2917469506728039,"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."}}