Bibliographic record
Abstract
A large-scale experimental, state of the art storage facility was constructed on the Macdonald Campus of McGill University. This storage facility will serve as a tool to further investigate many of the laboratory experiments performed in agricultural and food science topics, by providing a representation of actual storage facilities in use in the industry today. The storage facility was fully instrumented to provide valuable data of the stored commodity and it's environment. A custom control software was developed with a user friendly graphical interface. This fully automated software allows data acquisition and control of temperature and relative humidity of the experimental storage facility. Experiments were performed and the control software provided an adequate temperature and relative humidity control. The controller was based on a conventional PID or proportional, integral and derivative controller. To further improve the control of the storage facility, a novel multivariable PID controller was developed using enthalpy as the process variable, which encompasses both temperature and relative humidity. The novel controller was tested using a mathematical model developed. Simulations were performed comparing the performance of the novel multivariable controller to two other conventional controllers. The results demonstrate that the novel multivariable PID controller is capable of controlling temperature and relative humidity better than the other two conventional control techniques.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".