A rapid system for rating white pine blister rust incidence, severity, and within-tree distribution in whitebark pine
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
Whitebark pine is an ecologically important high-elevation tree species distributed across much of the western United States and Canada. Unfortunately, this species is now undergoing rapid decline in many portions of itsrange due to an exotic disease, white pine blister rust. The objective of this research was to develop a practical, time efficient, yet accurate, method for rating white pine blister rust disease severity in whitebark pine. The system provides estimates of disease severity at the single tree or stand level, and of the within-tree distribution of infection. It can also be used to provide an overall estimate of disease incidence in a stand. Results of our rapid rating system were compared with a more time-consuming canker counting method. Overall estimates of disease severity using the rapid rating system and the canker-counting system were comparable. Both mean total canker counts and % incidence were highly correlated with mean total disease severity rating scores.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it