{"id":"W4206771039","doi":"10.1093/nargab/lqab123","title":"FILER: a framework for harmonizing and querying large-scale functional genomics knowledge","year":2022,"lang":"en","type":"article","venue":"NAR Genomics and Bioinformatics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; Weston Brain Institute","keywords":"Scale (ratio); Genomics; Computer science; Functional genomics; Data science; Computational biology; Biology; Genome; Geography; Genetics; Cartography; Gene","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":[0.0201402,0.004887388,0.004479834,0.009011571,0.002220207,0.01007706,0.01704995,0.004830769,0.0200118],"category_scores_gemma":[0.0302803,0.00387586,0.008381544,0.00801459,0.003671907,0.01410996,0.01836657,0.005782382,0.01666444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00351689,"about_ca_system_score_gemma":0.004984847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01677063,"about_ca_topic_score_gemma":0.01380289,"domain_scores_codex":[0.9903515,0.001871961,0.001572559,0.002382892,0.003084523,0.0007365821],"domain_scores_gemma":[0.9865991,0.005749542,0.0008241055,0.004342023,0.001400344,0.001084973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003137407,0.0006025703,0.005140649,0.006565049,0.001396538,0.002831526,0.002610375,0.07110447,0.02062962,0.1103043,0.5240912,0.2515863],"study_design_scores_gemma":[0.001513554,0.0003950361,0.003461482,0.00162448,0.0004042124,0.001758733,0.001057605,0.2971455,0.02243902,0.2338715,0.4352413,0.001087448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001813847,0.0009748029,0.5910475,0.0008975827,0.0001920145,0.000653599,0.03889904,0.362146,0.00337556],"genre_scores_gemma":[0.03687442,0.001744707,0.6829357,0.001577258,0.0001888734,0.002619819,0.2218936,0.04829109,0.003874532],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0201402,"threshold_uncertainty_score":0.1065128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02949434952622089,"score_gpt":0.253449076832666,"score_spread":0.2239547273064452,"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."}}