Wavelength-modulated differential laser photothermal radiometry for blood glucose measurements
Bibliographic record
Abstract
A Wavelength-Modulated Differential Laser Photothermal Radiometer (WM-DPTR) technique was used for non-invasive blood glucose monitoring in the mid-IR range, where the prominent absorption peak is glucose specific and isolated from other interfering peaks in human blood. The WM-DPTR method consists of the out-of-phase modulated excitation at two discrete wavelengths 9.5 μm and 10.4 μm (near the peak and the baseline of glucose absorption), generated from two quantum cascade lasers (QCL) and the differential emission detection through a thermal-wave upconversion process via a HgCdZnTe (MCZT) detector (2-5 μm). The differential method suppresses the background signal and reduces source-detection interference, thus enhancing glucose detection sensitivity. The results from aqueous glucose phantom (0–440 mg/dl) measurements demonstrate that both amplitude and phase of the WM-DPTR signal can be used for glucose detection. The dynamic range and the sensitivity of the glucose detection are influenced greatly by the laser intensity ratio and modulation frequency. The optimal intensity ratio for high sensitivity is ~1. Other laser intensity ratios increase dynamic range but reduce sensitivity. Sensitivity increases with frequency.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".