On-line rheology of cell cultures in a bioreactor
Bibliographic record
Abstract
In: Proceeding of 8th World Congress of Chemical Engineering (WCCE8), August 23-29, Montréal, Quebec, Canada. Eds. Canadian Society for Chemical Engineering. (Ontario, Canada), ISBN: 0-9208044-44-6, Session: Rheology in Chemical Processing & Chemical Product Design, L.2225, 2009 Abstract: Cellular cultures require an in-depth knowledge of biological and physical parameters to control and optimize the process. Among the physical parameters, viscosity and rheological behaviour are of first importance. This study describes implementation and results obtained with an experimental on-line rheological device mounted on a bioreactor. Description of the set-up and experimental calibration with well-defined Newtonian fluids are presented. An example of a cellular culture (E. coli) is then proposed enlightening the influence of biological activity on rheological behaviour and the need for on-line measurement. coli. In: Proceeding of 8th World Congress of Chemical Engineering (WCCE8), August 23-29, Montréal, Quebec, Canada. Eds. Canadian Society for Chemical Engineering. (Ontario, Canada), ISBN: 0-9208044-44-6, Session: Rheology in Chemical Processing & Chemical Product Design, L.2225, 2009Abstract: Cellular cultures require an in-depth knowledge of biological and physical parameters to control and optimize the process. Among the physical parameters, viscosity and rheological behaviour are of first importance. This study describes implementation and results obtained with an experimental on-line rheological device mounted on a bioreactor. Description of the set-up and experimental calibration with well-defined Newtonian fluids are presented. An example of a cellular culture (E. coli) is then proposed enlightening the influence of biological activity on rheological behaviour and the need for on-line measurement. coli.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".