Miniaturization and Automation of an Internally Cooled Coated Fiber Device
Bibliographic record
Abstract
The internally cooled coated fiber device was miniaturized to allow its direct introduction into a gas chromatography injector, while maintaining a reasonable lifetime of the septum. The device was robust, and its fiber, which was accommodated in an 18-gauge needle, was reproducibly used for more than 100 injections without any coating failure. The fiber temperature was controlled within 5 degrees C of the preset value by use of a temperature controller, a solenoid valve, and stainless steel tubings with different inner diameter. The device was mounted and used on the CTC CombiPAL autosampler with minor modifications, such as enlarging the hole of the needle guide of the autosampler and coupling the temperature control system of the device to the autosampler through a logic circuit. The device was validated with the back equilibration of hydrocarbons preloaded in the fiber in air. The automation of the internally cooled coated fiber device provided the feasibility of high throughput for the analysis of analytes in complex matrixes that required simultaneous heating of the sample matrixes and cooling of the fiber coating.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".