{"id":"W2026251865","doi":"10.1016/j.aca.2014.11.029","title":"In vivo solid phase microextraction sampling of human saliva for non-invasive and on-site monitoring","year":2014,"lang":"en","type":"article","venue":"Analytica Chimica Acta","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":114,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Solid-phase microextraction; Chemistry; Chromatography; Detection limit; Analyte; Sample preparation; Extraction (chemistry); Solid phase extraction; Analytical Chemistry (journal); Mass spectrometry; Gas chromatography–mass spectrometry","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":[0.0003076319,0.0004851056,0.0003357037,0.00009793807,0.0001782249,0.000344845,0.0002534819,0.0004547542,0.0007827306],"category_scores_gemma":[0.0002436855,0.0001844608,0.00030133,0.000117675,0.0002286919,0.000249466,0.000181845,0.0004581054,0.0003477555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001185127,"about_ca_system_score_gemma":0.000420655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003804234,"about_ca_topic_score_gemma":0.0007495935,"domain_scores_codex":[0.9997442,0.00008456428,0.000008773964,0.00006868113,0.00006620235,0.0000275878],"domain_scores_gemma":[0.9998889,0.00003285474,0.0000213009,0.00002181804,0.00002377597,0.00001140446],"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":[0.0005577411,0.0000748347,0.0004377922,0.00002860055,0.000007477731,0.00001993875,0.00002234998,0.00004393046,0.9949613,0.00001766924,0.00004913109,0.003779224],"study_design_scores_gemma":[0.00002013653,0.001382115,0.004076207,0.000004173871,0.00004606014,0.0002174392,0.00006153133,0.00153131,0.9916209,0.00007565813,0.0009578305,0.000006604014],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9576757,0.002386407,0.03741012,0.0002125239,0.0001329666,0.0001678674,0.0007798774,0.0002062447,0.001028274],"genre_scores_gemma":[0.9738385,0.00153496,0.02082512,0.0001613756,0.0000436329,0.0001804127,0.0004211731,0.0000367231,0.002958013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007827306,"threshold_uncertainty_score":0.002618492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02062271414514856,"score_gpt":0.3365909064308395,"score_spread":0.315968192285691,"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."}}