Two-year response of American chestnut (<i>Castanea dentata</i>) seedlings to shelterwood harvesting and fire in a mixed-oak forest ecosystem
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.
Full frame distilled prediction
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.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: ObservationalConsensus signal: Observational
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.550
- Threshold uncertainty score
- 0.996
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.299 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
The American chestnut (Castanea dentata (Marsh.) Borkh.) was once an important tree species in the eastern United States prior to its devastation by the chestnut blight. The American Chestnut Foundation will soon release seeds that are blight resistant. However, the necessary site requirements for restoration efforts have not yet been explored. The goal of this study was to evaluate the survival and growth of chestnut seedlings within a diverse forest management regime. Seedlings were experimentally grown for 2 years in three mixed-oak forests subjected to thinning, burning, thinning followed by burning, and an untreated control. Seedling biomass parameters were most influenced by treatments that increased light availability. Soil chemistry and texture parameters were also correlated (p < 0.05) with chestnut biomass. Thus, site fertility should also be considered in reintroduction efforts. While site quality may influence growth, light conditions appear to be overwhelmingly important. Therefore, we recommend that American chestnut seeds be planted in areas with moderate to high light conditions (recently disturbed), with low surrounding competing vegetation (possibly after a burn) for optimal growth benefits.
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.
The record
- Venue
- Canadian Journal of Forest Research
- Topic
- Plant and Fungal Interactions Research
- Field
- Biochemistry, Genetics and Molecular Biology
- Canadian institutions
- not available
- Funders
- not available
- Keywords
- Chestnut blightThinningBiomass (ecology)SeedlingEnvironmental sciencePrescribed burnUnderstoryBlightFagaceaeVegetation (pathology)AgronomyForestryAgroforestryBotanyBiologyGeographyCanopy
- Has abstract in OpenAlex
- yes