Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The properties of a thin sheet of poly(dimethylsiloxane) (PDMS) membrane as an extraction phase were examined and compared to solid-phase microextraction (SPME) PDMS-coated fiber for application to semivolatile analytes in direct and headspace modes. This new PDMS extraction approach showed much higher extraction rates because of the larger surface area to extraction-phase volume ratio of the thin film. Unlike the coated rod formats of SPME using thick coatings, the high extraction rate of the membrane SPME technique allows larger amounts of analytes to be extracted within a short period of time. Therefore, higher extraction efficiency and sensitivity can be achieved without sacrificing analysis time. In direct membrane SPME extraction, a linear relationship was found between the initial rate of extraction and the surface area of the extraction phase. However, for headspace extraction, the rates were somewhat lower because of the resistance to analyte transport at the sample matrix/headspace barrier. It was found that the effect of this barrier could be reduced by increasing either agitation, temperature, or surface area of the sample matrix/headspace interface. A method for the determination of PAHs in spiked lake water samples was developed based on the membrane PDMS extraction coupled with GC/MS. A linearity of 0.9960 and detection limits in the low-ppt level were found. The reproducibility was found to vary from 2.8% to 10.7%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.000 |
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 it