Spectral examination of a multiple-flame photometric detector for use in chromatography
Bibliographic record
Abstract
An examination of the emission spectra produced in a novel multiple-flame photometric detector (mFPD) was performed and directly compared to spectra obtained from a conventional single-flame FPD mode. Through monitoring a broad spectral range from 250 to 850 nm, it was found that the mFPD produces sulfur emission predominantly as S2*, but HSO* can also be isolated in the red spectral region. Further, phosphorus emission in the mFPD was found to stem from HPO*, while carbon emission was attributed to CH* and C2*. Finally, background emission in the mFPD was determined to be from OH*. Qualitatively, these finding agree very well with the species found in a conventional single-flame FPD. However, quantitatively, the mFPD spectra consistently produced analyte emission bands that were relatively more intense, by as much as a factor of 3. In contrast with this, hydrocarbon spectra in the mFPD yielded significantly reduced relative intensities, owing to decreased C2* emission. As well, aromatic and aliphatic hydrocarbons produced much more similar distributions of CH* and C2* emission in the mFPD than in the conventional single-flame FPD mode. The results indicate that a relative reduction of C2 radical and an increase of oxidized carbon in the analytical flame of the mFPD could play a central role in the observed quenching-resistant behavior of this detector.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".