Bibliographic record
Abstract
Blister rust (Cronartium ribicola) entered Europe about 300 years after eastern white pine (Pinus strobus) was first planted in Europe. North America imported millions of infected seedlings after blister rust was firmly established throughout Europe. Blister rust probably entered into western North America on multiple occasions and spread throughout British Columbia (BC) by about 1930. Two large saw mills solely cutting western white pine (P. monticola) started in the 1920s with the main production for matches. Blister rust surveys in the 1940s painted a poor picture for the future of western white pine in BC, so it was discriminated against in forest management plans. Harvest volumes declined and the 2 mills ceased production about 1960. Selection of resistant clones from mature parents occurred between 1948 and 1960, but when it was evident that mature tree resistance was not likely to be in their seedlings the program was terminated. A program based on screening seedlings was started in 1983. The selected seedlings are hypothesized to possess age-related resistance that is being expressed at an early age. These and the better parents are incorporated into orchards. Key words: Cronartium, white pine, surveys, match blocks, rust resistance, PR proteins
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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".