{"id":"W2984769480","doi":"10.1093/nar/gkz933","title":"Xenbase: deep integration of GEO & SRA RNA-seq and ChIP-seq data in a model organism database","year":2019,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Wellcome Trust; Wellcome","keywords":"Biology; RNA-Seq; Organism; Database; RNA; Computational biology; Model organism; Genetics; Gene; Gene expression; Transcriptome; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000926777,0.0001306869,0.0001838308,0.0001150936,0.00006756265,0.00002762745,0.0005216104,0.0001259862,0.00006787783],"category_scores_gemma":[0.0002486326,0.0001194223,0.00002305406,0.0001746425,0.0001680799,0.000004003449,0.001327644,0.0002288262,0.00002184542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000179998,"about_ca_system_score_gemma":0.0001261245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002822983,"about_ca_topic_score_gemma":0.0006850605,"domain_scores_codex":[0.9985319,0.0001052413,0.0002308351,0.0005295938,0.0002789502,0.0003234357],"domain_scores_gemma":[0.9985489,0.0000373511,0.00004549582,0.001132892,0.0001586114,0.00007670831],"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":[0.00008696801,0.00006273472,0.006390872,0.00004509839,0.0000271202,0.00000113237,0.0002495132,0.00006865049,0.9880942,0.0002533669,0.0004489852,0.004271427],"study_design_scores_gemma":[0.007670044,0.001884874,0.1081015,0.0003013083,0.00008373042,0.00004671443,0.00370438,0.1664827,0.665702,0.005922035,0.03829268,0.001807998],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959482,0.001198905,0.0009005523,0.000179718,0.00004058086,0.000305722,0.0002896642,0.000001815212,0.001134872],"genre_scores_gemma":[0.9929369,0.001376782,0.00458366,0.00005232049,0.00005738666,0.00001142101,0.0004714334,0.00002533347,0.0004847776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3223921,"threshold_uncertainty_score":0.4869901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0716304473230731,"score_gpt":0.349149408186832,"score_spread":0.2775189608637589,"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."}}