{"id":"W1968325101","doi":"10.1021/ac990746j","title":"Calibration of Membrane Extraction for Air Analysis","year":2000,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Chemistry; Partition coefficient; Calibration; Extraction (chemistry); Analyte; Membrane; Chromatography; Constant (computer programming); Analytical Chemistry (journal); Biological system; Diffusion; Thermodynamics; Statistics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001057173,0.0001756915,0.0004056455,0.00003175075,0.00004147015,0.000009709152,0.0001533037,0.000232408,0.006694259],"category_scores_gemma":[0.0001973216,0.000171571,0.0004714403,0.0005631351,0.00008738238,0.00009110296,0.0000108761,0.000182186,0.00001150539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004276613,"about_ca_system_score_gemma":0.00001930504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001473032,"about_ca_topic_score_gemma":7.529237e-7,"domain_scores_codex":[0.9987084,0.000006855639,0.0004585444,0.0003248097,0.0002321821,0.0002692041],"domain_scores_gemma":[0.9991289,0.0002407304,0.00006505902,0.0003083879,0.00007775432,0.0001792151],"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":[0.000340761,0.0003345851,0.0005355716,0.0006378443,0.00168157,0.000009823121,0.00004467291,0.07322174,0.9202487,0.001007672,0.0006048628,0.001332167],"study_design_scores_gemma":[0.0002013917,0.000006776188,0.00003714988,0.000007807856,0.0006726909,0.000002201722,0.00001687101,0.4904839,0.507077,0.00008803064,0.00126983,0.0001362836],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8887643,0.00005655425,0.05362177,0.0005194738,0.00001828477,0.0001338851,0.0000942252,0.0001894302,0.05660213],"genre_scores_gemma":[0.9810074,0.00001224449,0.0004958726,0.00004757112,0.0001570851,0.000009141245,0.0001744377,0.00001712345,0.01807911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4172622,"threshold_uncertainty_score":0.9942138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0114485494789219,"score_gpt":0.2574743341724774,"score_spread":0.2460257846935555,"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."}}