Effect of plant-derived smoke water and potassium nitrate on germination of understory boreal forest plants
Bibliographic record
Abstract
This experiment assessed the effects of plant-derived smoke water, potassium nitrate (KNO3), and their combined effect on germination of cold-stratified and non-stratified seed from 18 native boreal forest plant species. Seeds were treated with smoke water diluted to 1:20, 0.1% KNO3, and smoke water + KNO3. Nine species responded positively to smoke water; these responses were dependent on the type of stratification, and three of these species only had a positive response to smoke water + KNO3 solution. Five species responded positively to KNO3 and four of those were associated with smoke water + KNO3 solution. Smoke water induced germination of several species, but only for seeds that had been previously cold-stratified. Vaccinium myrtilloides Michx. had the largest increase in germination using smoke water and the most reduced germination using KNO3. The interactions between smoke water, KNO3, and stratified seeds are not well understood. The effects and applications of smoke water and KNO3 (or other nitrogen sources) should be further researched to determine alternative approaches to restoration of disturbed boreal forest ecosystems.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".