Object: Revision of TEN project.
Bibliographic record
Abstract
chromatic dispersion equalizer for high bit rate communication systems ” as well as the relevant support letters from TeraXion dated June 6th, 2005 and August 31st, 2005. As per the request of the selection committee, the scheduling of the project work plan was revised to reach well-defined milestones every 6 months as detailed in section 4 of the proposal. A new paragraph listing the objectives and deliverables was also added to the project description on pages 10-11 (section 4, paragraph 6- Milestones). Please note that, considering the delays in the funding, we have modified the starting date of the project that is now November 1st 2005. We would also like to address below the comments of the committee listed in your letter. 1) "Le projet semble très exploratoire (ex. compte tenu du temps et de l’effort requis dans les simulations à Queen’s) et donc ne semble pas être prêt pour un transfert." We acknowledge that there was a lack of explanation on the link between the numerical simulations performed at Queen's and the experimental work done at Laval and we would like to thank the committee for giving us the opportunity to clarify this point. FBG-based dispersion compensating devices have been studied for many years for standard modulation formats (NRZ, RZ) and performance indicators such as phase ripple are now available to define requirements for these devices. As soon as the project is funded, the design and fabrication of the FBG devices will start at Laval using these criteria.
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 | 0.020 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.250 | 0.206 |
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".