{"id":"W2006928412","doi":"10.1016/j.chroma.2014.02.070","title":"Cooled membrane for high sensitivity gas sampling","year":2014,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Chemistry; Membrane; Chromatography; Analytical Chemistry (journal); Reproducibility; Sampling (signal processing); Extraction (chemistry); Volumetric flow rate; Gas chromatography; Detection limit; Humidity; Sample preparation","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":[],"consensus_categories":[],"category_scores_codex":[0.0001517884,0.0001398187,0.0003386426,0.0001855349,0.00003689781,0.00001899377,0.0001216619,0.0001075257,0.000004808323],"category_scores_gemma":[0.000210449,0.0001227593,0.000208323,0.0002251541,0.00006058942,0.0001270219,0.00001309555,0.0002174613,0.000001349957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002480309,"about_ca_system_score_gemma":0.000002248253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.340555e-7,"about_ca_topic_score_gemma":0.000001230544,"domain_scores_codex":[0.9991969,0.00001297425,0.0003302651,0.00008217635,0.0001488471,0.0002287817],"domain_scores_gemma":[0.9991918,0.0003493884,0.0001373759,0.000150849,0.0001026485,0.00006795733],"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":[0.00002765395,0.00001970979,0.000138733,0.0001143045,0.0001067752,0.00000687928,0.00001923035,0.01067761,0.9816919,0.0009123374,0.0003706868,0.005914177],"study_design_scores_gemma":[0.0008305072,0.0001001378,0.0004645452,0.000105734,0.0000488157,0.0001504087,0.00003409608,0.003581916,0.978241,0.01189432,0.004353485,0.0001950124],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8293381,0.0001489286,0.1697675,0.0001019542,0.0002005617,0.00006794831,0.000005402096,0.0002513203,0.0001183851],"genre_scores_gemma":[0.9621233,0.00008233338,0.03757379,0.00002672322,0.0001602776,0.000002604716,0.000001167485,0.00002855028,0.000001217344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1327853,"threshold_uncertainty_score":0.500598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008866598122791223,"score_gpt":0.2191401001463342,"score_spread":0.2102735020235429,"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."}}