Forest disease records on eastern white pine in Atlantic Canada: 1950 to 1996
Bibliographic record
Abstract
Between 1936 and 1996, the Forest Insect and Disease Survey (FIDS) of the Canadian Forest Service of Natural Resources Canada surveyed eastern white pine (Pinus strobus L.) throughout Atlantic Canada. During those years, FIDS reported its insect and disease findings in a wide variety of regional and national reports and in the scientific literature. The National Forest Health Database contains these electronic records and indicates the distribution and relative importance of forest diseases and fungi for many tree species in Atlantic Canada. This paper is a frequency analysis of the fungal diseases recorded from the Atlantic provinces in the National Forest Health Database and reported in the various Maritime, Newfoundland and national FIDS reports. The significant eastern white pine diseases (e.g., white pine blister rust Cronartium ribicola J.C. Fisch.) that are established in Atlantic Canada as well as other diseases that are found elsewhere in Canada, but not yet in the Atlantic provinces are discussed. Occurrence data for 40 of the less frequently collected fungal species are presented in a summary table. Key words: white pine blister rust, Cronartium ribicola, eastern white pine, Pinus strobus, Scleroderris canker, Gremmeniella abietina, Annosus root rot, Heterobasidion annosum, white pine root decline, Leptographium procerum, needle cast, Lophodermium pinastri, brown felt fungus, Septobasidium pinicola, Atlantic Canada, forest disease
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".