{"id":"W4239977244","doi":"10.1021/ac051035q","title":"Time-Weighted Average Water Sampling with a Solid-Phase Microextraction Device","year":2005,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Chemistry; Solid-phase microextraction; Sampling (signal processing); Aqueous solution; Analytical Chemistry (journal); Mass transfer; Chromatography; Diffusion; Coating; Naphthalene; Passive sampling; Calibration; Mass spectrometry; Gas chromatography–mass spectrometry; Thermodynamics","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":["insufficient_payload"],"category_scores_codex":[0.0001409609,0.0001635758,0.0001525083,0.00001317758,0.0000973065,0.00004688525,0.0002420884,0.0001367081,0.00247484],"category_scores_gemma":[0.00002580829,0.0001143019,0.00004556334,0.0001140567,0.0002350506,0.0001841502,0.0001630309,0.000249613,0.001674304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002288254,"about_ca_system_score_gemma":0.000005324952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002887479,"about_ca_topic_score_gemma":0.000002271491,"domain_scores_codex":[0.9988086,0.00001073841,0.0002025749,0.0003557218,0.000249338,0.0003730303],"domain_scores_gemma":[0.9994718,0.00003571671,0.00003680662,0.0003443416,0.00001015687,0.0001011839],"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":[0.00004861371,0.0002164954,0.001118409,0.0000174492,0.00003073089,0.00002164808,0.00008717839,0.0006965874,0.9951851,0.000001872535,0.000725236,0.001850615],"study_design_scores_gemma":[0.0003749668,0.00002685573,0.000169945,0.00001507592,0.00003241777,0.00003079594,0.00002748473,0.006893586,0.9743133,0.00009012684,0.0178065,0.0002189459],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934762,0.000004843394,0.001302484,0.001207947,0.000009652349,0.0000540749,0.000003021354,0.0002373389,0.003704462],"genre_scores_gemma":[0.9922899,0.000002064185,0.004118364,0.00008558155,0.0001135193,0.00000690515,0.00002101375,0.00001640622,0.003346261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02087186,"threshold_uncertainty_score":0.999103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02428646740916106,"score_gpt":0.3100896394922085,"score_spread":0.2858031720830474,"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."}}