{"id":"W4281477116","doi":"10.1093/nar/gkac383","title":"CFM-ID 4.0 – a web server for accurate MS-based metabolite identification","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Environmental Health Sciences; Genome Canada; Canadian Institutes of Health Research; National Institutes of Health; Alberta Machine Intelligence Institute; Compute Canada","keywords":"Biology; Identification (biology); Metabolite; Computational biology; Web server; Database; The Internet; World Wide Web; Computer science; Biochemistry","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":[0.003644245,0.004414135,0.002199397,0.006240399,0.001224087,0.003000705,0.004870227,0.00320967,0.05064713],"category_scores_gemma":[0.006266804,0.001682296,0.002547303,0.003454346,0.0005445497,0.003809543,0.003047833,0.002629537,0.06090441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001536051,"about_ca_system_score_gemma":0.002985361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004319017,"about_ca_topic_score_gemma":0.004786544,"domain_scores_codex":[0.9981914,0.0001760838,0.0001526633,0.0005517014,0.0006758665,0.0002522782],"domain_scores_gemma":[0.9977456,0.0004523367,0.0002769681,0.0005439113,0.00078639,0.0001947582],"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":[0.003556491,0.0003287626,0.006168525,0.002844413,0.0005707045,0.000805409,0.00018664,0.003461279,0.05993596,0.004023907,0.8035268,0.1145911],"study_design_scores_gemma":[0.001207998,0.0005850318,0.01349293,0.0008034504,0.0003500708,0.001974546,0.0001452046,0.1031261,0.1646651,0.02442297,0.6883982,0.0008284046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.008276256,0.002571401,0.1127255,0.0004448352,0.0004128466,0.0007371532,0.296474,0.5640209,0.01433705],"genre_scores_gemma":[0.03432802,0.001124996,0.2473731,0.001390151,0.0002029221,0.001430237,0.6594064,0.0449096,0.009834508],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.05064713,"threshold_uncertainty_score":0.1694315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04932090300937642,"score_gpt":0.3558929868266221,"score_spread":0.3065720838172457,"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."}}