Bioreactor controlled by PI algorithm and operated with a perfusion chamber to support endothelial cell survival and proliferation
Bibliographic record
Abstract
This paper reports the optimization of a perfusion bioreactor system previously reported by us (Chouinard et al., 2009). The implementation of a proportional-integral (PI) controller algorithm to control oxygen concentration and pH is presented and discussed. P and I values used by the controller were first estimated using a First-Order-Plus-Dead-Time (FOPDT, Matlab Simulink) and then tuned manually. A new gas exchanger design compatible with the PI controller was introduced and validated to decrease interaction between the injected gases and overall inertia of the system. The gas exchanger was used to adjust both pH and dissolved oxygen (DO) concentration. This new bioreactor system allowed real-time PI control over pH and DO concentration at different flow rates (from 2 to 70 mL min(-1)). Cell viability and proliferation were investigated to validate the updated bioreactor design and performance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".