East Meets West - LOI Signing Ceremony between UiTM and the University of Ottawa, Canada / PM Khas Dr. Angeline Ranjethamoney Vijayarajoo ... [et al.]
Bibliographic record
Abstract
Rome was not built in a day. Neither was the tie that has been fostered between UiTM Cawangan Negeri Sembilan (UiTMCNS) and the University of Ottawa, Canada. Spearheaded by the Academy of Language Studies, Seremban Campus, the negotiations on collaborative efforts between UiTM and the University of Ottawa took months of hard work and countless late-night meetings to cater to the different time zones of both countries. After many negotiations and much goodwill in force, they culminated in the signing of a Letter of Intent (LOI) between the two universities. The historic date was the 25th May 2022, 9.00 am at the Tuanku Syed Sirajuddin Chancellery Building, UiTM Shah Alam. On the side of UiTM, the Vice Chancellor gave a speech followed by the President (equivalent to the Vice Chancellor) of the University of Ottawa, before the signing of the document took place. Both heads of Universities, Prof. Datuk Ts. Dr. Roziah Mohd Janor and Mr. Jacques Fremont, were visibly pleased with the visit and the signing event. As for the ownership of the LOI, it is held and headed by Prof. Dr. Yamin Yasin, the Rector of UiTMCNS. The event was also graced by the attendance of Mr. Khairil Azwan Abu Mansor, Senior Principal Assistant Secretary of the Ministry of Higher Education, as well as Mrs. Nur Ezira Mahadi, Principal Assistant Secretary of the Ministry of Foreign Affairs.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.002 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.310 | 0.085 |
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".