Bibliographic record
Abstract
This report describes the development of a 3-stage plan for refurbishment of the planar motion mechanism (PMM). The purpose behind refurbishing the PMM is to make improvements that will translate into more accurate test results. This report looks at increasing the PMM structural stiffness by replacing the yaw mechanism, designing and building a new modular dynamometer for use on the PMM, and the issues associated with the current software for the PMM as well as possible improvements to be made in replacement software. Stage 1 of the refurbishment involves the design of the dynamometer. A cruciform structure was used as it showed greater stiffness then the present trapezoidal structure in finite element analysis. Other improvements made to the dynamometer include the use of button load cells as opposed to cantilever for increased stiffness. Stage 2 involves incorporating two tapered roller bearings into the yaw mechanism of the PMM. One bearing has a particularly large diameter that sits between the dynamometer and the PMM frame. This increases the stiffness of the PMM by allowing the dynamometer to be held closer to the PMM frame and through a wider contact surface. In stage 3 of the refurbishment issue with the current control software are addressed. The most important of these issues is the lack of documentation for the software. It is felt that rewriting the software would be the best solution. Stage 3 also lists some possible improvements that can be made to rewritten software such as the separation of the software into two entirely separate programs instead of having one program with two parts, as is the present case. Also, the future expansion of the PMM is considered in the software improvements by having excess control channels programmed into the software that would allow additional hardware controllers to be used.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.047 | 0.018 |
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".