{"id":"W4405613379","doi":"10.1021/acs.analchem.4c04060","title":"Introducing “Identification Probability” for Automated and Transferable Assessment of Metabolite Identification Confidence in Metabolomics and Related Studies","year":2024,"lang":"en","type":"review","venue":"Analytical Chemistry","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Common Fund; Pacific Northwest National Laboratory; National Institute of Environmental Health Sciences; National Institutes of Health; National Cancer Institute; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; National Institute of General Medical Sciences; Battelle","keywords":"Metabolomics; Identification (biology); Context (archaeology); Chemistry; Metabolome; Ambiguity; Metabolite; Computer science; Computational biology; Data mining; Chromatography","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":[0.05224018,0.001906816,0.001984803,0.007924037,0.001571215,0.00839487,0.004149496,0.003453264,0.003196236],"category_scores_gemma":[0.2238078,0.001177646,0.002322286,0.005692141,0.004431533,0.01482178,0.00867983,0.005192358,0.001155386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002277341,"about_ca_system_score_gemma":0.002754976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001767275,"about_ca_topic_score_gemma":0.001124629,"domain_scores_codex":[0.9493942,0.02222106,0.005371663,0.008563069,0.01338272,0.001067297],"domain_scores_gemma":[0.7686381,0.158112,0.02235165,0.02921103,0.01987356,0.001813606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001115289,0.0005442315,0.05869051,0.001289001,0.0006267604,0.0006962878,0.002438986,0.1402637,0.01506467,0.2362935,0.008263235,0.5347137],"study_design_scores_gemma":[0.0001011286,0.0004170677,0.01244672,0.0004724937,0.000217677,0.0007721141,0.0005513842,0.6167205,0.02202901,0.3311219,0.01478669,0.0003632748],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009885104,0.0003658966,0.9850907,0.0007695327,0.0001014061,0.0001382121,0.0003122822,0.00156029,0.001776498],"genre_scores_gemma":[0.2631594,0.0003457838,0.7336105,0.0005013921,0.0002516262,0.0004663175,0.0006677716,0.0003921941,0.0006051137],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05224018,"threshold_uncertainty_score":0.2762758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0377758686506033,"score_gpt":0.3855997681327949,"score_spread":0.3478238994821916,"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."}}