{"id":"W4317743512","doi":"10.1093/nargab/lqad003","title":"Differential Expression Enrichment Tool (DEET): an interactive atlas of human differential gene expression","year":2023,"lang":"en","type":"article","venue":"NAR Genomics and Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Vector Institute; SickKids Foundation; University of Toronto","funders":"National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Centre for Applied Genomics; Genome Canada","keywords":"Computational biology; Expression (computer science); Pipeline (software); Gene expression; Gene; Computer science; Differential (mechanical device); Biology; Gene expression profiling; DEET; Information retrieval; Data mining; 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":[0.002445725,0.001718546,0.001726275,0.006632308,0.0009244793,0.001426273,0.001991658,0.0006563969,0.02450541],"category_scores_gemma":[0.005026546,0.0008597596,0.002052912,0.006118332,0.000457544,0.0009176845,0.00253039,0.001749454,0.00616386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008527592,"about_ca_system_score_gemma":0.00201353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00187549,"about_ca_topic_score_gemma":0.005017678,"domain_scores_codex":[0.9981661,0.0004754858,0.0001624952,0.0004839082,0.000561549,0.0001504846],"domain_scores_gemma":[0.9977285,0.00131202,0.0002613613,0.0003161136,0.000276185,0.0001058866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002376393,0.0002754666,0.03512955,0.01112834,0.00271308,0.001385449,0.001405382,0.01762634,0.1927567,0.0243115,0.3809205,0.3299712],"study_design_scores_gemma":[0.0006788248,0.0004500961,0.0655404,0.0007946498,0.001498086,0.002454117,0.0003667416,0.06834607,0.1076967,0.03692508,0.7148952,0.0003540599],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.03171165,0.007058828,0.5385583,0.0006443396,0.0006298068,0.0006337366,0.3127338,0.09017926,0.01785028],"genre_scores_gemma":[0.08794935,0.003408163,0.6937876,0.0006758939,0.0001689903,0.004612388,0.1907772,0.01142118,0.007199047],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.02450541,"threshold_uncertainty_score":0.08197874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009721680046971246,"score_gpt":0.2465778461921381,"score_spread":0.2368561661451669,"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."}}