{"id":"W4307468148","doi":"10.1093/nar/gkac919","title":"ChemFOnt: the chemical functional ontology resource","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada Foundation for Innovation; Genome Canada","keywords":"Ontology; Terminology; Resource (disambiguation); Computer science; Web resource; Chemical nomenclature; Biology; World Wide Web; Database; Information retrieval; Chemistry","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":[0.002442363,0.002676785,0.002043849,0.008374504,0.001689141,0.003909697,0.005088841,0.002618718,0.06392716],"category_scores_gemma":[0.007019855,0.001506927,0.002391261,0.009791543,0.0007656669,0.006339366,0.003722211,0.00292713,0.04596898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002935724,"about_ca_system_score_gemma":0.007069185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02066942,"about_ca_topic_score_gemma":0.01713933,"domain_scores_codex":[0.9982991,0.0002237371,0.0002784339,0.0002805719,0.000750613,0.0001675787],"domain_scores_gemma":[0.9976997,0.0007026789,0.0002389753,0.0004733458,0.0006311881,0.0002542099],"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":[0.0001853026,0.0001124994,0.0007709707,0.004865121,0.0001712178,0.0003400372,0.0002646855,0.001957878,0.005549177,0.04440738,0.8879157,0.0534599],"study_design_scores_gemma":[0.00005169132,0.000007335073,0.0004271488,0.0003823898,0.00003659302,0.0001495806,0.00005435456,0.001395222,0.001334451,0.01092747,0.9851854,0.00004846969],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.00133251,0.003283511,0.07111752,0.001328285,0.0006169635,0.0008805344,0.8077612,0.03925597,0.07442349],"genre_scores_gemma":[0.006322386,0.004235301,0.07800592,0.001113337,0.0001151899,0.001672645,0.8925992,0.007158493,0.008777548],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.06392716,"threshold_uncertainty_score":0.2138577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04142707278095025,"score_gpt":0.3114064103602251,"score_spread":0.2699793375792749,"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."}}