A case of extensive conifer needle browning in northwestern Ontario in 2012: Winter drying or freezing damage?
Bibliographic record
Abstract
In the spring of 2012, conifers in a large area in northwestern Ontario exhibited severe needle browning prior to budbreak, affecting more than 250 000 ha of forests north and west of Thunder Bay. Examination of weather data suggests that damage was caused by a combination of warm temperatures in March resulting in dehardening followed by freezing temperatures in April that were below a critical value. Damage was similar in nature to that observed in 2007 in northeastern Ontario, but in this case occurred earlier in the year and affected a larger area. Areas of northern Ontario where trees were affected were easily separated from those where no damage was observed using daily minimum temperature and cumulative growing degree day data. We suggest that a new term, winter freezing damage, be used to describe conifer needle and bud damage prior to budbreak when a period of warm temperatures in late winter/early spring followed by a period of sufficiently cold freezing temperatures causes damage to forest stands.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".