{"id":"W2101418868","doi":"10.1093/chromsci/40.3.140","title":"Automation of Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry Extraction of Eucalyptus Volatiles","year":2002,"lang":"en","type":"article","venue":"Journal of Chromatographic Science","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Chromatography; Chemistry; Solid-phase microextraction; Extraction (chemistry); Mass spectrometry; Gas chromatography; Eucalyptus; Gas chromatography–mass spectrometry; Sample preparation; Botany","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":[0.0005336448,0.0006100232,0.0005124977,0.0005226255,0.000218543,0.0004378727,0.0003067761,0.0002719419,0.000513814],"category_scores_gemma":[0.0006968175,0.0002639088,0.0003339894,0.000427435,0.0002747034,0.0002901349,0.0003958462,0.0004875489,0.00070128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002379171,"about_ca_system_score_gemma":0.0005424895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009244609,"about_ca_topic_score_gemma":0.001976151,"domain_scores_codex":[0.9990346,0.0001281458,0.00007697605,0.0002171972,0.0004541308,0.00008902339],"domain_scores_gemma":[0.9996076,0.0001363139,0.00004537346,0.00006436875,0.0001258207,0.00002042351],"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":[0.00008056784,0.00002955999,0.0007005301,0.00005142223,0.000007091718,0.00003355785,0.00001698394,0.0002181063,0.9861237,0.00004913913,0.00007014797,0.01261937],"study_design_scores_gemma":[0.0000151551,0.0001837286,0.01438996,0.000009035241,0.00002224125,0.0002500924,0.00001869072,0.003024335,0.9790567,0.0001561992,0.002857481,0.00001632838],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6751032,0.002089087,0.3118041,0.0002244664,0.0001318177,0.0008061122,0.002134332,0.003796769,0.003910239],"genre_scores_gemma":[0.6857825,0.001428126,0.3059519,0.0001601775,0.00004904642,0.0005476663,0.003497281,0.0002509674,0.002332396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009244609,"threshold_uncertainty_score":0.00282222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01430171218083566,"score_gpt":0.3031796793521342,"score_spread":0.2888779671712986,"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."}}