Kinetic Calibration Using Dominant Pre-equilibrium Desorption for On-Site and in Vivo Sampling by Solid-Phase Microextraction
Bibliographic record
Abstract
A new kinetic calibration was developed using dominant pre-equilibrium desorption by solid-phase microextracton. The calibration was based on isotropism between absorption and desorption, which was proved theoretically and experimentally in an aqueous solution and semisolid matrix. This approach allows for the calibration of absorption using desorption to compensate for matrix effects. Moreover, concentration profiles are initially proposed to verify isotropism between the absorption and desorption, while providing a linear approach to obtain time constants for the purpose of quantitative analysis. This linear approach is more convenient, robust, and accurate than the nonlinear version with the previously used time profiles. Furthermore, the target analytes are used as the internal standards; thus, radioactive or deuterated internal standards are not necessary. In addition, dominant pre-equilibrium desorption utilizes the pre-equilibrium approach and offers a shorter sample preparation time, which is typically suitable for in vivo sampling. This kinetic calibration method was successfully applied to prepare samples of polycyclic aromatic hydrocarbons in a flow-through system and in vivo pesticide sampling in a jade plant (Crassula ovata).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".