Proposition d’une méthodologie d’inventaire et de cartographie écologique; le cas de la MRC du Haut-Saint-Laurent
Bibliographic record
Abstract
Au Québec, les rapports entre écologie et aménagement sont encore ténus. La législation, après avoir privilégié la notion de conservation des sites, ne s'est dotée que récemment de lois d'aménagement impliquant des principes de planification écologique. Quant aux grands projets d'aménagement, ils n'ont généralement pas tiré profit des études écologiques qu'ils avaient pourtant suscitées. Un projet du Centre de recherches écologiques de Montréal (CREM) envisage une approche interactive où la cartographie des écosystèmes permet d'identifier les aptitudes du territoire ainsi que les zones de contraintes, mais ne saurait, seule, commander automatiquement les affectations et les types d'aménagement.
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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 | 0.019 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".