A reliable multi-nutrient model for the rapid production of high-density microalgal biomass over a broad spectrum of mixotrophic conditions
Bibliographic record
Abstract
The superior microalgal biomass productivities obtained under mixotrophic conditions have been widely demonstrated. However, to attain the full potential of the method, optimal conditions for biomass production and resource utilization need to be determined and successfully exploited throughout the process operation. Detailed kinetic mathematical models have often proved most efficient tools for predicting process behavior and governing its overall operation. This paper presents an extensive study for obtaining a highly reliable model for mixotrophic production of microalgae covering a wide set and range of nutritional conditions (10-fold the concentration range of Bold’s Basal Medium) and biomass yields up to 6.68 g.L −1 after only 6 days. The final reduced model includes a total of five state variables and nine parameters: model calibration resulted in very small 95% confidence intervals and relative errors below 5% for all parameters. Model validation showed high reliability with R 2 correlation values between 0.77 and 0.99.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 0.000 |
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".