Calibrating jack pine allometric relationships with simultaneous regressions
Bibliographic record
Abstract
Allometric equations for estimating foliage biomass, sapwood area, and branch basal area from tree diameters and crown lengths for jack pine ( Pinus banksiana Lamb.) in eastern Canada were calibrated using mixed models. A first model is presented that relates branch foliage biomass to branch diameter and relative position within the crown. These results show that a branch’s foliage biomass is inversely proportional to its depth within the crown. At the tree level, foliage biomass was found to be proportional to crown length and to vary with stem age and slenderness. Pipe model parameters (sapwood area and branch basal area to foliage biomass) were also calculated. The sapwood area to foliage biomass parameter is proportional to stand density, whereas branch basal area to foliage biomass is constant. The tree-level allometeric models were calibrated using a mixed-effects seemingly unrelated regression to account for between-model correlations.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".