{"id":"W2613847904","doi":"10.1038/nbt.3790","title":"Discovering and linking public omics data sets using the Omics Discovery Index","year":2017,"lang":"en","type":"letter","venue":"Nature Biotechnology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":222,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Biotechnology and Biological Sciences Research Council; National Institutes of Health; National Cancer Institute; National Institute of General Medical Sciences; European Molecular Biology Laboratory; Wellcome Trust","keywords":"Omics; Index (typography); Computational biology; Data science; Data mining; Computer science; Biology; Bioinformatics; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.005658556,0.0005374044,0.001135143,0.001310158,0.001433699,0.004130889,0.001506977,0.01200074,0.004630012],"category_scores_gemma":[0.03853631,0.0006735213,0.0009558107,0.001221439,0.002443734,0.004048039,0.001919604,0.02346384,0.006540885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00227483,"about_ca_system_score_gemma":0.001611573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001551137,"about_ca_topic_score_gemma":0.003020769,"domain_scores_codex":[0.9974485,0.0008736411,0.0003385128,0.0002564664,0.0008962587,0.0001864723],"domain_scores_gemma":[0.9712237,0.02220827,0.0009959376,0.001331196,0.00289621,0.001344662],"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":[0.0002236317,0.00007623524,0.001877574,0.00008979512,0.00006218544,0.001391964,0.0001184273,0.0003947347,0.0007081954,0.01002633,0.8993475,0.08568333],"study_design_scores_gemma":[0.0005051881,0.0001065204,0.002368601,0.0003883032,0.000118441,0.00357652,0.0003252641,0.009592374,0.00217538,0.1900122,0.7907064,0.000124658],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.001087206,0.002105596,0.003788348,0.9779759,0.01211073,0.00003428941,0.0003421126,0.0001622135,0.002393587],"genre_scores_gemma":[0.02701977,0.008698029,0.01737313,0.8308771,0.1020356,0.0003494156,0.0007521571,0.0002574394,0.0126375],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.998493,"threshold_uncertainty_score":0.02992564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02053145535458049,"score_gpt":0.2673348186949408,"score_spread":0.2468033633403603,"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."}}