405 nm Absorption Detection in Nanoliter Volumes
Bibliographic record
Abstract
Analytical UV absorption detection for microfluidic devices, capillary electrophoresis, and even high-performance liquid chromatography is hampered by the small detection volumes, short absorption paths, and the need to sample at a high rate with a stable background and low noise. Fiber-loop ring-down spectroscopy (FLRDS) permits absorption detection of dilute liquid samples in volumes as small as a few nanoliters, while being insensitive to light source fluctuations and permitting a millisecond temporal resolution. We demonstrate a FLRDS based detection scheme that is compatible in dimensions (<200 microm absorption path, 6.0 nL detection volume) and optical design (405 nm detection wavelength, fiber coupled) with existing separation systems. An optical/fluidic interface has been built that allows injection of laser light into the loop while also permitting delivery of the sample. The detection limit of tartrazine was determined to be 5 microM (30 fmol) corresponding to an absorption of 0.11 cm(-1). Equivalent results were obtained when detecting myoglobin, a heterocyclic pharmaceutical ingredient, and 5.17 microm diameter polystyrene beads.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".