{"id":"W2053343067","doi":"10.1021/jf025577+","title":"Sampling and Monitoring of Biogenic Emissions by Eucalyptus Leaves Using Membrane Extraction with Sorbent Interface (MESI)","year":2002,"lang":"en","type":"article","venue":"Journal of Agricultural and Food Chemistry","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Tenax; Sorbent; Extraction (chemistry); Membrane; Eucalyptus; Polydimethylsiloxane; Chromatography; Chemistry; Gas chromatography; Environmental science; Adsorption; Botany; Organic chemistry; Biology","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":[0.0001895805,0.0002469214,0.0002664225,0.000198977,0.0001727729,0.0001807418,0.0001620089,0.0001876592,0.0002343534],"category_scores_gemma":[0.0001441063,0.0001326776,0.000163187,0.0001970319,0.0001156577,0.0002278205,0.0002116033,0.000193124,0.0001583186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001802614,"about_ca_system_score_gemma":0.0001765429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007740408,"about_ca_topic_score_gemma":0.001737443,"domain_scores_codex":[0.9998534,0.00002515039,0.000009373651,0.00005817604,0.00003989206,0.00001388746],"domain_scores_gemma":[0.9999297,0.00002173358,0.00001865968,0.000007883339,0.0000116272,0.00001034413],"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":[0.0000323121,0.000005185109,0.0006948422,0.00001982765,0.00000238258,0.00000709099,0.00000863592,0.00004880284,0.9966373,0.00000925021,0.000006410489,0.002527899],"study_design_scores_gemma":[0.000004893951,0.0001294764,0.01325304,0.000002697176,0.00001060335,0.0001396231,0.0000162505,0.001307992,0.9845829,0.0000224174,0.0005223258,0.000007750002],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785497,0.0005450691,0.01967575,0.00002680579,0.000005686717,0.00003118619,0.0003803216,0.0001170823,0.0006685163],"genre_scores_gemma":[0.9413482,0.0005803984,0.05565023,0.00003858082,0.000006217265,0.0000811858,0.0005122078,0.00003237841,0.001750613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007740408,"threshold_uncertainty_score":0.001539052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01866997631211065,"score_gpt":0.2259689400660862,"score_spread":0.2072989637539756,"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."}}