{"id":"W4385488201","doi":"10.1101/2023.07.31.549036","title":"Comparative Analysis of Methods to Reduce Activation Signature Gene Expression in PBMCs","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Immune Response and Inflammation","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Université de Montréal","funders":"Courtois Foundation; Centre Hospitalier Universitaire de Québec; Université Laval; Schlumberger Foundation; Fonds de Recherche du Québec - Santé; Michael J. Fox Foundation for Parkinson's Research","keywords":"Transcriptome; Peripheral blood mononuclear cell; Ex vivo; Gene expression; Gene expression profiling; Biology; Gene signature; Gene; Transcription (linguistics); In vivo; Regulation of gene expression; Cell biology; Computational biology; In vitro; Genetics","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":[0.001084948,0.0005897878,0.000607287,0.0006189932,0.0003357126,0.0008952833,0.0003182282,0.0003423434,0.002089545],"category_scores_gemma":[0.001180741,0.0001997501,0.0006351864,0.000593586,0.0003877575,0.0002517807,0.0003709115,0.0008912613,0.001264097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004039386,"about_ca_system_score_gemma":0.0004603629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003726867,"about_ca_topic_score_gemma":0.0006270942,"domain_scores_codex":[0.9986326,0.0002809626,0.0001151216,0.0003276235,0.0005267246,0.0001168612],"domain_scores_gemma":[0.9991849,0.0003454117,0.0001249165,0.0001032727,0.0002017825,0.00003970004],"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":[0.000213777,0.00002129282,0.0004368441,0.0001680589,0.00001984934,0.00001965373,0.00003294486,0.0001855298,0.9933537,0.00007639395,0.0001362601,0.005335706],"study_design_scores_gemma":[0.00001216271,0.0002823857,0.007490885,0.00002195219,0.00007076171,0.000132911,0.00006567051,0.001008878,0.9844823,0.0001284139,0.006287282,0.00001639941],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7505065,0.01024986,0.2205097,0.0005643264,0.0006454612,0.0006668185,0.009883522,0.0008930399,0.006080836],"genre_scores_gemma":[0.6902164,0.007253817,0.2664261,0.0009547215,0.0003357847,0.00283674,0.02216023,0.001279851,0.008536419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002089545,"threshold_uncertainty_score":0.006990194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03629576938250553,"score_gpt":0.3163077113254666,"score_spread":0.2800119419429611,"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."}}