(Invited) A Frequency Domain Optofluidics Dissolved Oxygen Sensor
Bibliographic record
Abstract
Concentration of Dissolved oxygen (DO) is an important indicator of water quality. Fluorescence quenching is a commonly used optical method to measure DO. Steady-state fluorescence intensity measurements are easy to be influenced by acquisition artifacts, which makes determination of absolution DO values difficult. We developed a miniaturized, optofluidics frequency-domain DO sensor that measures fluorescence quenching using fluorescence lifetime changes of Ruthenium (Ru(dpp)3Cl2) rather than intensity. Dissolved oxygen is quantified by the phase shift between excitation modulation and emission modulation through process. Compact, low cost components such as diode lasers and photodiodes have been used for the potential of scalable distributed sensing applications. The sensor is evaluated using water samples with different oxygen concentrations. Experimental results show that the lifetime measured in frequency domain corresponds well to dissolved oxygen concentration. Long-term experimental demonstrates that the proposed sensor remains stable in the presence of photobleaching; since the measured phase shift is not affected by reduction of the fluorescence intensity. The sensitivity of the DO measurement is also enhanced through the total internal reflection design.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".