An Emerging Digital Library Platform for Canada’s North.
Bibliographic record
Abstract
Digital libraries (DLs) play a crucial role in both reducing barriers, such as spatial barriers, and increasing our ability to provide access to content particularly to remote users with access to the Internet. The proposed work on a digital library for communities in Canada’s North is a step in this direction. This poster will provide an overview on the progress and development of a DL and present key findings including lessons learned during the course of this research work. Les bibliothèques numériques (BN) jouent un rôle crucial à la fois dans la réduction des obstacles, tels que les barrières spatiales, et dans l’augmentation de notre capacité à fournir un accès aux contenus, particulièrement aux utilisateurs éloignés munis d’un accès à Internet. Cette affiche porte sur une bibliothèque numérique destinée aux collectivités du Nord . Ce travail donne un aperçu des progrès et du développement de la bibliothèque numérique et présente les principales conclusions, y compris les leçons apprises au cours de ce travail de recherche.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.004 |
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".