Deposition of a Sorbent into a Recession on a Solid Support To Provide a New, Mechanically Robust Solid-Phase Microextraction Device
Bibliographic record
Abstract
To date, solid-phase microextraction (SPME) fibers used for in vivo bioanalysis can be too fragile and flexible, which limits suitability for direct tissue sampling. As a result, these devices often require a sheathing needle to prepuncture robust sample matrixes and protect the extraction phase from mechanical damage. To address this limitation, a new SPME device is herein presented which incorporates an extraction phase recessed into the body of a solid needle. This device requires no additional support or shielding during puncture events through protective tissue. The presented device was thoroughly tested, being fired at 90 m·s –1 through fish scales, forced through vial septa, and employed in a targeted study of polyunsaturated fatty acids in salmon where the protective outer skin was repetitively punctured during sampling. Finally, the recessed SPME device was applied to an on-site application for the tissue analysis of wild muskellunge. With this advancement, rapid, minimally invasive, and easily executed in vivo SPME is now possible opening the door to near endless sampling opportunities.
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.
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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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".