{"id":"W2048951656","doi":"10.1016/j.chroma.2013.07.110","title":"Determination of polycyclic aromatic hydrocarbons in solid matrices using automated cold fiber headspace solid phase microextraction technique","year":2013,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Solid-phase microextraction; Chemistry; Extraction (chemistry); Chromatography; Fiber; Gas chromatography; Sample preparation; Certified reference materials; Matrix (chemical analysis); Solid phase extraction; Gas chromatography–mass spectrometry; Detection limit; Mass spectrometry; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004753505,0.000260324,0.0006210515,0.0006171158,0.00005032548,0.00005213441,0.0002666259,0.000256198,0.0001275928],"category_scores_gemma":[0.0001511339,0.0002476245,0.0003011718,0.0007769038,0.0001116433,0.0004053859,0.00003311555,0.0003885941,0.000004030522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001963392,"about_ca_system_score_gemma":0.0001518596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005012989,"about_ca_topic_score_gemma":0.000001872942,"domain_scores_codex":[0.9975961,0.00007721322,0.001350582,0.000195157,0.0004511951,0.0003297523],"domain_scores_gemma":[0.997833,0.0002283594,0.001485202,0.0002307827,0.00005142364,0.0001712292],"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":[0.00003486698,0.0004732833,0.001030411,0.0002090678,0.00009215488,0.00004060395,0.0001069692,0.000006173111,0.9969867,7.463502e-7,0.00007273435,0.0009462162],"study_design_scores_gemma":[0.001161199,0.00006573268,0.0005552082,0.0009610167,0.0001250628,0.0005936395,0.0001366065,0.0189436,0.9766316,0.0005022715,0.00007863432,0.0002454059],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764736,0.0002820146,0.02219921,0.00007304378,0.00004008828,0.000176754,0.000002455532,0.00007904074,0.0006738132],"genre_scores_gemma":[0.8748629,0.00004228023,0.1249483,0.00001370014,0.00004886381,0.00001888284,0.000002580593,0.00003006596,0.00003234129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1027491,"threshold_uncertainty_score":0.9999976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01721235508263816,"score_gpt":0.3386427497741083,"score_spread":0.3214303946914702,"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."}}