{"id":"W2130666470","doi":"10.1093/bib/bbn042","title":"Gene-set analysis and reduction","year":2008,"lang":"en","type":"review","venue":"Briefings in Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Cancer Institute; Astellas Pharma; Genome Alberta; Canada Research Chairs; Muttart Foundation; University of Alberta; Fondation pour la Recherche Médicale; Roche Organ Transplant Research Foundation; Kidney Foundation of Canada; Canadian Institutes of Health Research; Genome Canada","keywords":"Microarray analysis techniques; Gene; Set (abstract data type); Computational biology; DNA microarray; Microarray; Microarray databases; Gene expression; Computer science; Gene chip analysis; Phenotype; Biology; 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":[0.003057019,0.001714643,0.003595633,0.006256609,0.0005823259,0.002317884,0.00336473,0.0008024054,0.005824569],"category_scores_gemma":[0.004609467,0.0006569533,0.00288256,0.008260215,0.00170066,0.00147372,0.001551553,0.002153791,0.007280922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001441468,"about_ca_system_score_gemma":0.001449931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329511,"about_ca_topic_score_gemma":0.001184397,"domain_scores_codex":[0.9973153,0.0005479937,0.0002449132,0.0006117925,0.001200226,0.00007981176],"domain_scores_gemma":[0.9982777,0.0007592492,0.0001063575,0.0002884834,0.0005317311,0.00003646402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008513154,0.00006037842,0.0008372898,0.007653347,0.0004187565,0.0002220049,0.0001537685,0.009673869,0.01304563,0.05086936,0.03161046,0.88537],"study_design_scores_gemma":[0.00006499619,0.0001490971,0.005787997,0.001246681,0.0003537381,0.001780211,0.0002497567,0.02548178,0.0264815,0.2059925,0.7322341,0.0001776711],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.002601314,0.1700871,0.8024061,0.001857651,0.001262341,0.0006093085,0.004608557,0.002357395,0.01421017],"genre_scores_gemma":[0.02506489,0.1668686,0.7852398,0.0009952821,0.0009614725,0.00186972,0.009708264,0.0007253313,0.008566578],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.006256609,"threshold_uncertainty_score":0.01948512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01980434045847544,"score_gpt":0.2729433399758128,"score_spread":0.2531389995173373,"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."}}