Changes in blister rust infection and mortality in whitebark pine over time
Bibliographic record
Abstract
Whitebark pine (Pinus albicaulis Engelm.), a keystone species in subalpine ecosystems of western North America, is under threat across its range from white pine blister rust, mountain pine beetle, fire exclusion, and climate change. Loss of whitebark pine is predicted to have cascading effects on many ecosystem services. We remeasured 115 whitebark pine plots in the Canadian Rocky Mountains to determine whether infection and mortality rates from blister rust were changing over time and (or) latitude. Average rust infection of trees among plots increased from 42% in 2003–2004 to 52% in 2009, while mortality increased from 18% to 28%. In eight plots that have been measured three times, infection increased from 43% of live trees in 1996 to 70% in 2003 and 78% in 2009. Mortality increased from 26% to 65% in the same time period. Overall, infection and mortality have increased 3%/year over the 13 years of the study. Incidence of infection and mortality was highest among plots in the southern part of the study area, particularly on the western side of the Continental Divide. The slowing rates of infection and mortality that we found suggest that some level of natural selection may already be occurring in areas with high levels of both.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".