Standard‐free kinetic calibration for rapid on‐site analysis by solid‐phase microextraction
Bibliographic record
Abstract
In this study, a new calibration method, standard-free kinetic calibration, is proposed for rapid on-site analysis by solid-phase microextraction (SPME), based on the diffusion-controlled mass transfer model and equilibrium extraction. With this calibration method, all analytes can be directly calibrated with only two samplings. The feasibility of this calibration method was validated in a standard aqueous solution flow-through system and a standard gas flow-through system. The distribution coefficients of five polycyclic aromatic hydrocarbons (PAHs), including naphthalene, acenaphthene, fluorene, anthracene, and pyrene, between water and the PDMS fiber coating were determined and the concentrations of the PAHs in the flow-through system were successfully calibrated with the proposed standard-free calibration method. The extracted amounts of BTEX (benzene, toluene, ethylbezene, o-xylene) at equilibrium were also successfully calibrated with this method with two rapid sampling periods at 5 and 10 s. Compared with the previous calibration methods for rapid on-site analysis by SPME, this method does not require a standard to calibrate the extraction, nor does it require additional equipment to control or measure the flow velocity of the sample matrix. In addition, all of the extracted analytes can be quantified without considering whether the system reached equilibrium. The newly proposed standard-free kinetic calibration approach enriched the calibration methods available for on-site analysis by SPME.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".