A Brief Report on the Canadian Chapter: Signing of the MoU between UiTM and the University of Ottawa, Canada. / PM Khas Dr Angeline Ranjethamoney Vijayarajoo
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
This memorable and historical journey began on the 15th of August, 2022. The members of the team who left for Canada on government service comprised the following people: Prof Yamin Yasin (our Rector, UiTMCNS) Ts Dr Noorlis Ahmad (Deputy Rector, Academic Affairs, UiTMCNS) Dr Siti Nor Atika Baharin (Liaison Officer, UiTM Global, UiTMCNS) Associate Professor Dr Angeline Ranjethamoney Vijayarajoo (UiTMCNS, APB Seremban,) We began our journey from Kuala Lumpur to Canada, with a transit stop- over at Doha. After this, our first point of entry to Canada was Montreal, where we had a connecting flight to Toronto. Toronto was where our first official duties began on the 15th of August, 2022. However, the focus of this article is the signing of the MoU between the University of Ottawa and Universiti Teknologi MARA, Malaysia. Hence, this article will only focus on the MoU Ceremony between Universiti Teknologi MARA (UiTM) and the University of Ottawa (UO).
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 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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