Is direct seeding a good option for regeneration in British Columbia?
Bibliographic record
Abstract
In British Columbia, forest tenure holders have the obligation to reforest harvested areas, and the government invests in regeneration in areas damaged by wildfire or mountain pine beetle (MPB). Direct seeding (or direct sowing) is a process by which woodlands are established or re-established by sowing tree seeds at their final growing location. Direct seeding is being re-introduced in BC as an alternative to planting. Many factors affect the emergence and survival of seedlings, including temperature, precipitation, soil structure, predation and vegetation competition, all of which interact with the biological characteristics of the tree species. In field trials, site selection, site preparation, seed selection, vegetation control, increasing seeding density, sowing with alternate foods, and sowing with cover crop have been shown to improve seedling establishment. . However, the effectiveness of these techniques may vary with species, local environment, and location. Therefore, more research is needed before direct seeding can be applied broadly for regeneration in BC. Specific recommendations include: 1) more field trials; 2) enhanced communication and cooperation among research agencies and licencee holders; 3) modelling of germination response to varying conditions; 4) reduction in seed cost; and, 5) improvements in machine efficiency.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".