Non-wood Forest Products Based on Extractives - A New Opportunity for the Canadian Forest Industry Part 1: Hardwood Forest Species
Bibliographic record
Abstract
Forest resources are among the most important of Canada (in the case of Québec, nearly 90% of the territory). Innovation represents an essential challenge for the Canadian forest industry, which is presently undergoing major changes towards finding new solutions for recovery. The processing of forest biomass has become increasingly relevant along with the popular concept of biorefineries. This concept should include the development of novel technologies based on forest extractives. Bioactive molecules are readily available through eco-friendly extraction processes using various types of forest residues including barks which are generated in significant quantities by the industry. This literature review offers a glimpse into the hardwood boreal forest with a particular focus on industrial species. We are adopting an ethno-pharmacological approach prior to presenting existing data on bioactive molecules from various sources, along with results from our own laboratory. In conclusion, this paper clearly demonstrates the need for further research on bioactive molecules from Canadian forest species since there remains an important lack of reliable data.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".