Data from: Effect of a severe cold spell on overwintering survival of an invasive forest insect pest
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Data from a study of a servere cold event in February 2023 on the survival of hemlock woolly adelgid (Adelges tsugae Annand) from four populations in Canada. Cold temperatures can play a significant role in the range and impact of pest insects. Severe cold events can reduce the size of insect outbreaks or in some cases even cause outbreaks to end. Measuring the precise impact of cold events, however, can be difficult because estimates of insect mortality are often made at the end of the winter season. In late January, 2023 long-term climate models predicted a significant cold event to occur over eastern North America. We used this event to evaluate the immediate impact on hemlock woolly adelgid overwintering mortality at four sites on the northern edge of the insects invaded range in eastern North America. We observed complete mortality, partial mortality and no effect of the cold event that correlated with the location and strength of the cold event. Our data also showed lack of support for preconditioning of overwintering adelgids as impacting their overwintering survival following this severe cold event. Finally, we compared the climatic conditions at our sites to historical weather data. The cold event observed in February 2023 resulted in the coldest temperatures observed at these sites, including the period within which hemlock woolly adelgid invaded these sites, suggesting cold conditions, especially under anthropogenic climate forcing, may not be a limiting factor in determining the ultimate northern range of hemlock woolly adelgid in eastern North America.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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 it