News from the Québec Monitoring Network on Environmental Impacts of Forest Biomass Harvesting
Bibliographic record
Abstract
L’utilisation de la biomasse pour la production de bioénergie représente un emesure clé dans l’effort international pour atteindre zéro émissions nettes en CO2 d’ici 2050. Selon l’Agence internationale de l’énergie, la biomasse est la source de 55 % de l’énergie renouvelable produite au monde actuellement et 6 % de la demande globale, toutes sources d’énergie confondues. Au Canada, la matière ligneuse résiduelle issue de la récolte forestière et de l’industrie de transformation du bois représente la source principale de biomasse et contribue environ à 5 % de la production d’énergie. L’utilisation de la biomasse forestière a un grand potentiel de développement au Canada, mais des inquiétudes demeurent quant aux impacts environnementaux et sociaux,surtout en ce qui a trait au bilan carbone et à la fertilité des sols forestiers à la suite du prélèvement des résidus de coupe. C’est dans cette optique que le Service canadien des forêts, en collaboration avec plusieurs partenaires, dont l’Université Laval, a mis en place le Réseau de dispositifs de suivi des impacts environnementaux de la récolte de biomasse forestière au Québec.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.061 | 0.015 |
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".