A Sensitive Small-Volume UV/Vis Flow Cell and Total Absorbance Detection System for Micro-HPLC
Bibliographic record
Abstract
An optical multichannel absorbance detection system suitable for micro-HPLC is described. The detection system includes a flow cell with detection volume of 30 nL and path length of 12 mm. A fiber optic spectrometer with charge-coupled device array is used to collect spectral information at 1 Hz frequency. Signal-to-noise ratios are enhanced through the use of large bandwidth total absorbance signals, while linearity and spectral resolution are maintained. Theoretical predictions of bandwidth dependent signal-to-noise ratios of the total absorbance signal are compared to experimental observations, showing that optimum total absorbance signal bandwidths occur at 2.8 σ abs for a Gaussian absorption band under light noise limited conditions. This bandwidth is much larger than bandwidths used in most commercial detectors. The detection system is applied to the separation of 2,4-dinitophenylhydrazones of organic carbonyls sampled from tropospheric air samples. For these hydrazones, a bandwidth of 181 nm is used for detection and calibration, which results in more universal hydrazone detection.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.015 |
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".