{"id":"W4378386373","doi":"10.3389/fimmu.2023.1135859","title":"Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets","year":2023,"lang":"en","type":"article","venue":"Frontiers in Immunology","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Killam Trusts","keywords":"Sepsis; Transcriptome; Computational biology; Bioinformatics; Compendium; Gene; Biology; Medicine; Gene expression; Genetics; Immunology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00617136,0.002322342,0.002912944,0.008788409,0.002061727,0.003723175,0.002530213,0.001329768,0.009099429],"category_scores_gemma":[0.0126139,0.0009974997,0.003917926,0.00560646,0.001089962,0.001505849,0.004175561,0.002639252,0.006508351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001479034,"about_ca_system_score_gemma":0.00905769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005493955,"about_ca_topic_score_gemma":0.01813686,"domain_scores_codex":[0.996295,0.0006046073,0.0007710714,0.001228165,0.000874985,0.0002261892],"domain_scores_gemma":[0.9930285,0.003652537,0.0008102306,0.001054258,0.001097553,0.0003569946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00244948,0.0002913674,0.04627943,0.07571185,0.004057603,0.005964014,0.004272135,0.02551712,0.2949024,0.02536812,0.2795859,0.2356007],"study_design_scores_gemma":[0.0004270902,0.0004465592,0.0524507,0.005566202,0.00269234,0.003037286,0.0008720121,0.01964832,0.0321633,0.01273948,0.8694816,0.0004751644],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.02257848,0.01028916,0.0874521,0.0005964775,0.0007175038,0.000673669,0.8526765,0.01660696,0.008409244],"genre_scores_gemma":[0.02326753,0.003538087,0.147991,0.0004549038,0.00007018429,0.001457649,0.819854,0.001948466,0.001418256],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.009099429,"threshold_uncertainty_score":0.03263766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2077896324167479,"score_gpt":0.4113717312351409,"score_spread":0.2035820988183931,"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."}}