A PDMS sheath flow cuvette for high‐sensitivity LIF measurements in CE
Bibliographic record
Abstract
A simple method for producing a sheath flow cuvette in PDMS suitable for post-column detection in CE is described. Two types of cuvette were investigated. In the first, the sheath flow channel had a round cross-section of approximately 635 microm diameter, whereas the second cuvette had a 300x300 microm(2) square channel. Both cuvettes produced laminar flows that ensheathed the separation capillary's effluent allowing sensitive fluorescence measurements. The elasticity of the PDMS allowed the 300x300 microm(2) square sheath flow channel to expand uniformly and accommodate the larger 330-340 microm od round separation capillary, producing a self-aligning cuvette with robust mechanical properties. With this cuvette, linear calibrations of over five orders of magnitude and 15-30 zmol fluorescein detection limits were obtained for 12 and 50 microm id capillaries.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".