Bibliographic record
Abstract
A survey of the health of whitebark pine (Pinus albicaulis Engelm.) was conducted throughout its range in British Columbia, Canada. Over 3 years, 24 070 trees were examined for mortality, incidence of white pine blister rust (Cronartium ribicola J.C. Fisch.), or other damage. About 19% of whitebark pine (>1.3 m in height) were dead, and another 31% had active blister rust infections. Tests of relationships between the proportion of healthy, infected, or dead trees and elevation, latitude, and longitude produced mixed results. The ratio of healthy to infected whitebark pine varies considerably across the province, with a trend of increasing incidence from west to east. Losses to mountain pine beetle (Dendroctonus ponderosae Hopkins) proved minor, but bark stripping by mammals was common. Whitebark pine seedlings (<1.3 m in height) revealed lower rates of mortality (11%) and rust infection (4%) than larger trees. However, the pioneer species whitebark pine was found in less than half the regeneration plots and was usually outnumbered by subalpine fir (Abies lasiocarpa (Hook.) Nutt.). The combination of mature tree mortality, lack of suitable substrate for regeneration, and the incursion of climax species indicates a continued decline in whitebark pine populations in British Columbia.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".