Microalgae on display: a microfluidic pixel-based irradiance assay for photosynthetic growth
Bibliographic record
Abstract
Microalgal biofuel is an emerging sustainable energy resource. Photosynthetic growth is heavily dependent on irradiance, therefore photobioreactor design optimization requires comprehensive screening of irradiance variables, such as intensity, time variance and spectral composition. Here we present a microfluidic irradiance assay which leverages liquid crystal display technology to provide multiplexed screening of irradiance conditions on growth. An array of 238 microreactors are operated in parallel with identical chemical environments. The approach is demonstrated by performing three irradiance assays. The first assay evaluates the effect of intensity on growth, quantifying saturating intensity. The second assay quantifies the influence of time-varied intensity and the threshold frequency for growth. Lastly, the coupled influence of red-blue spectral composition and intensity is assessed. Each multiplexed assay is completed within three days. In contrast, completing the same number of experiments using conventional incubation flasks would require several years. Not only does our approach enable more rapid screening, but the short optical path avoids self-shading issues inherent to flask based systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".