Incidence and ecology of the chaga fungus (<i>Inonotus obliquus</i>) in hardwood New England – Acadian forests
Bibliographic record
Abstract
Inonotus obliquus (Ach. ex Pers.) Pilát is a fungal pathogen of birch trees (Betula spp.) and other hardwoods that produces a sterile conk known colloquially as chaga. Chaga has medicinal value as an anti-mutagen and for gastro-peptic relief. Chaga harvesting has recently increased throughout its natural range in North America, including the White Mountain National Forest (WMNF). There is currently a lack of knowledge on chaga resource incidence and ecology in North America, which this project sought to rectify. Two surveys were conducted in 2017 and 2018 in the WMNF, totaling 2611 sampled trees. Positive correlations were found between chaga presence and mean stand tree age, diameter at breast height, and elevation. Overall chaga frequency was low (3.75%); however, sclerotia were widely distributed throughout the study area, with infected trees clustering. Chaga presence did not correlate with stand-level species composition or annual basal area increment, though it did appear with significantly greater frequency in yellow birch trees compared with other birch species. Additional damages related to biotic and abiotic stressors did not correlate with chaga presence, except for those resulting directly from chaga presence. These results have important silvicultural and forest management implications for chaga harvest practices across its North American range.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".