EXPERIENCE WITH CAPSTONE PROJECTS BASED ON COLDFIRE MICROCONTROLLERS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract – This paper describes the experience of the author in supervising capstone undergraduate projects that have used microcontroller chips based on the Cold-Fire processor architecture, along with supporting hard-ware and software. Six capstone design projects are se-lected for illustration, and these projects have been pur-sued by a total of nineteen students under the supervision of the author in the Department of Electrical and Com-puter Engineering at Queen’s University between 2013 and 2017. After summarizing the selected projects to pro-vide the context, this paper highlights the supervisory role of the author to provide potentially useful insights to oth-er potential project supervisors. A retrospective assess-ment is provided for the decision to use ColdFire-based platforms in these projects, along with some reflections on the experience. Considerations for platform selection by the author in future projects are also outlined.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it