{"id":"W2662820349","doi":"10.1039/c7an00718c","title":"Towards on-site analysis of complex matrices by solid-phase microextraction-transmission mode coupled to a portable mass spectrometer via direct analysis in real time","year":2017,"lang":"en","type":"article","venue":"The Analyst","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Solid-phase microextraction; Mass spectrometry; DART ion source; Spectrometer; Transmission (telecommunications); Mode (computer interface); Complex matrix; Phase (matter); Analytical Chemistry (journal); Chromatography; Chemistry; Materials science; Computer science; Gas chromatography–mass spectrometry; Physics; Optics; Telecommunications; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004154949,0.0002710604,0.000961498,0.001012878,0.0003286353,0.0001414737,0.0008468094,0.0001132913,0.007433147],"category_scores_gemma":[0.0000170366,0.0002095064,0.0006428204,0.002740646,0.00007085973,0.0001066352,0.00006998913,0.0002025633,0.00002701896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001531449,"about_ca_system_score_gemma":0.00002598782,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01233898,"about_ca_topic_score_gemma":0.0007642115,"domain_scores_codex":[0.9980017,0.0000396451,0.0006427873,0.0005331218,0.0004188981,0.0003638502],"domain_scores_gemma":[0.9973767,0.0001009464,0.0005871279,0.001691381,0.00009601327,0.0001478284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001287811,0.0003872355,0.003196502,0.00001801268,0.003120234,0.000006016742,0.00007369103,0.001537934,0.9899516,0.00006393337,0.0008653919,0.0006507319],"study_design_scores_gemma":[0.0009110716,0.000137614,0.01243938,0.0000398442,0.01698702,0.000002064024,0.00005966936,0.5639235,0.3996203,0.0005120783,0.00466677,0.0007006541],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9247691,0.00005595029,0.02601749,0.001085653,0.000005904903,0.0002331824,0.0007793412,0.0001213121,0.04693208],"genre_scores_gemma":[0.9935366,0.0001966135,0.002971031,0.00003924432,0.00003240983,0.00005046656,0.000621265,0.0000231859,0.002529168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5903312,"threshold_uncertainty_score":0.994238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01555604747849984,"score_gpt":0.3468491181006112,"score_spread":0.3312930706221114,"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."}}