{"id":"W1965316721","doi":"10.1021/es802198z","title":"International NMR-Based Environmental Metabolomics Intercomparison Exercise","year":2008,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":155,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Metabolomics; Principal component analysis; Multivariate statistics; Data verification; Sample (material); Multivariate analysis; Metabolite; Environmental chemistry; Environmental science; Data mining; Chemistry; Computer science; Chromatography; Artificial intelligence; Biochemistry; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06744054,0.001271982,0.001143746,0.002129101,0.002893044,0.002876965,0.003234715,0.001624381,0.003459884],"category_scores_gemma":[0.03528026,0.0005885173,0.001409658,0.002790827,0.001521427,0.002579628,0.004788741,0.001798959,0.001960525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001800791,"about_ca_system_score_gemma":0.006749039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002268778,"about_ca_topic_score_gemma":0.003903213,"domain_scores_codex":[0.9657782,0.01914903,0.002572633,0.004278733,0.0072227,0.0009987707],"domain_scores_gemma":[0.9645153,0.006218627,0.002954491,0.01208797,0.01309245,0.001131091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004435119,0.003577503,0.03947484,0.001196923,0.001246665,0.0005314338,0.003483829,0.02615342,0.3667807,0.01935499,0.01340125,0.5203634],"study_design_scores_gemma":[0.0007608159,0.01094241,0.1165857,0.0003425883,0.001023604,0.0007735536,0.00321555,0.02328771,0.5901074,0.02153753,0.2309394,0.0004836488],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2336171,0.001534415,0.7001968,0.002920543,0.0006583007,0.01084672,0.005144422,0.002001225,0.04308039],"genre_scores_gemma":[0.2878791,0.0006694074,0.6856458,0.0006635256,0.0002334461,0.008885769,0.007805354,0.0003748327,0.007842786],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06744054,"threshold_uncertainty_score":0.3566639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007232944344645661,"score_gpt":0.2186726317314475,"score_spread":0.2114396873868018,"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."}}