{"id":"W2966344753","doi":"10.21105/joss.01182","title":"VIVO: a system for research discovery","year":2019,"lang":"es","type":"article","venue":"The Journal of Open Source Software","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"National Institutes of Health","keywords":"In vivo; Computational biology; Data science; Computer science; Biology; Biotechnology","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":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.009501043,0.000215576,0.0006391721,0.0001979357,0.0005397858,0.002955207,0.007750083,0.0001243336,0.0000266106],"category_scores_gemma":[0.0008164552,0.0001245023,0.0002580143,0.0004979366,0.0002020207,0.001748254,0.002323204,0.0006594947,0.0001371307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001705161,"about_ca_system_score_gemma":0.0006084789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002060715,"about_ca_topic_score_gemma":0.000007362506,"domain_scores_codex":[0.9964619,0.0008956396,0.0007029467,0.0002744963,0.001023394,0.0006416787],"domain_scores_gemma":[0.99326,0.003914321,0.0007132168,0.001086455,0.0008986174,0.0001273567],"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":[0.01131373,0.001672939,0.1861275,0.009711511,0.003666164,0.0005402962,0.09550143,0.01294185,0.008268218,0.1321647,0.3064477,0.2316439],"study_design_scores_gemma":[0.01724628,0.01408778,0.04632436,0.02446278,0.001098614,0.007569483,0.1437773,0.01802357,0.01910869,0.0167926,0.6886129,0.002895652],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6030759,0.003876269,0.3822717,0.004786636,0.002552093,0.00196797,0.00002530405,0.00005653515,0.001387607],"genre_scores_gemma":[0.9838035,0.0001153643,0.007746906,0.0001698318,0.0004882598,0.000008084049,3.894841e-7,0.00003557264,0.007632094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3821652,"threshold_uncertainty_score":0.9980798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08423399063207367,"score_gpt":0.3737604722084825,"score_spread":0.2895264815764088,"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."}}