A height-growth and site-index model for interior spruce in the Sub-Boreal Spruce biogeoclimatic zone of British Columbia
Bibliographic record
Abstract
Height growth was modelled for spruce-dominated, even-aged stands in the Sub-Boreal Spruce biogeoclimatic zone of British Columbia, Canada, using both stem analysis (SA) and permanent sample plot (PSP) data. The model is based on a stochastic differential equation (SDE) formulation of the Bertalanffy–Richards growth equation. The SDE approach accounts for serial correlation and heterogeneous variance and makes hypothesis testing possible. Statistically significant differences in height–age trends between SA and PSP data were found that may be attributed to bias caused by dominance changes in SA trees. Error structure in SA and PSPs was also significantly different. Combining both data sources in a way that respects these different error structures reduced bias and increased precision. Four parametrizations were tested; the best was a polymorphic version. The final model fit the data well with no appreciable bias over the full range of ages and site qualities. The currently used spruce site-index model was found to underestimate growth and overestimate site index in young stands. The new model can be recommended for height prediction and site-quality assessment in interior spruce.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".