Individual fertilization response with social status and crown characteristics for western hemlock (<i>Tsuga heterophylla</i>)
Bibliographic record
Abstract
Due to their high variability, the growth responses of western hemlock ( Tsuga heterophylla (Raf.) Sarg.) stands to fertilization have been regarded as unresponsive or inconsistent. Tree-level fertilization response models for western hemlock were constructed to clarify the inconsistent stand-level responses, using extensive datasets from the United States and Canada. Tree growth in diameter and height, mortality, were assessed by fertilization, stand- and tree-level variables using generalized linear and nonlinear mixed-effects models. Western hemlock fertilization response was influenced not only by stand-level variables and application rates but also by tree social status and crown characteristics. Greater dominance and crown ratio in trees increased height growth responses but decreased diameter growth. The peak of fertilization effect on diameter growth was observed 3 years after application, while effect on height growth peaked at 6 years. Fertilization increased the overall mortality rate, but also ameliorated it for suppressed and steady-growing trees. These complicated fertilization responses of western hemlock may imply its tolerance and allocation strategy of resources at a given size and social status. The results highlight the importance of adopting a tree-level modeling approach to better understanding how western hemlock trees respond to fertilization, improving the accuracy of growth and yield prediction after fertilization.
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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 | 0.000 | 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) | 0.001 | 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".