Réalignement d’infrastructures côtières et restauration d’un marais salé en Nouvelle‑Écosse (Canada)
Bibliographic record
Abstract
Ce chapitre décrit un projet de réalignement d’une partie de la digue North‑Onslow, près de la ville de Truro au Canada. Ce projet visait plusieurs objectifs : réduire le coût d’entretien de la digue, améliorer la protection des infrastructures publiques et privées et renforcer la résilience face au changement climatique par la restauration d’une plaine inondable côtière. Ce chapitre a été rédigé par Kate Sherren, de la School for Resource and Environmental Studies, Dalhousie University, Halifax ; Tony Bowron, du Department of Environmental Science, Saint Mary’s University, Halifax, et de CB Wetlands and Environmental Specialists (CBWES Inc.), Terrance Bay ; Jennifer M. Graham, de CB Wetlands and Environmental Specialists (CBWES Inc.), Terrance Bay ; H.M. Tuihedur Rahman, du Department of Geography and Environmental Studies, Saint Mary’s University, Halifax et de la School for Resource and Environmental Studies, Dalhousie University, Halifax ; et Danika van Proosdij, du Department of Geography and Environmental Studies, Saint Mary’s University, Halifax.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".