{"id":"W2593783557","doi":"10.1038/srep44038","title":"In vivo microsampling to capture the elusive exposome","year":2017,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Waterloo","funders":"","keywords":"Exposome; Sampling (signal processing); Metabolomics; In vivo; Computational biology; Solid-phase microextraction; Mass spectrometry; Computer science; Chemistry; Chromatography; Biology; Medicine; Pathology; Gas chromatography–mass spectrometry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006044605,0.0008248027,0.0002874942,0.000309287,0.0004166186,0.0003615182,0.0003133006,0.0004702054,0.001825113],"category_scores_gemma":[0.0004069093,0.0002047576,0.000324859,0.0001775481,0.0003965136,0.0003359492,0.0003645103,0.0006188676,0.0004671327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000273324,"about_ca_system_score_gemma":0.0004491895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007579474,"about_ca_topic_score_gemma":0.00236969,"domain_scores_codex":[0.999714,0.00005723227,0.00002021391,0.0001063904,0.00006976252,0.00003243135],"domain_scores_gemma":[0.9996665,0.0001050559,0.00007141009,0.00007778565,0.00005697307,0.00002240507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004972816,0.00002387465,0.000568048,0.00003532744,0.00001001553,0.00001853602,0.00001744736,0.0000658783,0.9972384,0.0000941203,0.00004291715,0.001835793],"study_design_scores_gemma":[0.000008302503,0.0003343294,0.006401056,0.000006293687,0.00003593952,0.000150681,0.00003777582,0.001588617,0.9879937,0.0002040158,0.003231741,0.000007692443],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6604705,0.002329884,0.3300159,0.0005493901,0.0003250651,0.0008106151,0.00106947,0.0005629892,0.00386605],"genre_scores_gemma":[0.7778338,0.002964062,0.2072355,0.0008746833,0.0001655193,0.001373766,0.001711278,0.000248845,0.007592617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001825113,"threshold_uncertainty_score":0.006105661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01239573130092661,"score_gpt":0.2759587556980269,"score_spread":0.2635630243971003,"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."}}