Height growth and site index models for Pacific silver fir in southwestern British Columbia
Bibliographic record
Abstract
Following an exploratory examination of the variation in the height growth pattern using a singlevalued ratio, conventional polymorphic and climate-specific height growth and site index models were developed for Pacific silver fir (Abies amabilis [Dougl. ex Loud.] Forbes). The models were developed from stem analysis data obtained from 67 study plots, which were located over the entire elevation-continentality range of the species in southern coastal British Columbia. When tested against an independent data set consisting of 31 plots, the climate-specific models improved height and site index prediction compared to the conventional polymorphic models. The previously available model for Pacific silver fir was biased. It overestimated height before, and underestimated it beyond, the index age. It also underestimated height on low-productivity sites and overestimated it on high-productivity sites. In consequence, when this model was used to estimate site index from top-height and breast-height age, it underestimated site index before, and overestimated it beyond, the index age. Similarly, site index was overestimated on low-productivity sites and underestimated on high-productivity sites. The climate-specific models developed in this study are recommended for height and site index estimation of Pacific silver fir stands within a range of breast-height age from 15 to 160 years in southern coastal British Columbia.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".