Biophysical and potential vegetation growth surfaces for a small watershed in northern Cape Breton Island, Nova Scotia, Canada
Bibliographic record
Abstract
Surfaces of potential vegetation growth in this paper represent the spatial distribution of growing conditions (habitat) for six deciduous tree species native to the Clyburn River valley watershed of northeastern Cape Breton Island, Nova Scotia. Development of potential growth surfaces is based on integrating point calculations of (i) net potential solar radiation, (ii) net long-wave radiation, (iii) growing season degree-day accumulation, and (iv) mean summer soil water content with species-specific evaluations of long-term species environmental response. Functions describing potential species response to available environmental resources are based on generalised mathematical functions that scale species response values between 0 and 1, where 0 represents unsuitable growing conditions and 1, optimal growing conditions. Limitation effects of resource deficits on potential growth are addressed as a multiplication of individual environmental responses. Derived species distributions of potential growth are compared with aerial photo-interpreted distributions of forest vegetation found within the Clyburn River valley watershed. Modelled and photo-interpreted valley distributions demonstrate nearly similar geographic ranges. Actual percent cover for shade-tolerant species displays a positive correlation with modelled potential growth (r2 = 0.5). This is not the case for shade-intolerant species considered, whereby r2 [Formula: see text] 0.
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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".