Calibration and testing of a generalized process-based model for use in Portuguese eucalyptus plantations
Bibliographic record
Abstract
The work described in this paper aimed to establish a single set of parameter values for a process-based model (3-PG), applicable to Eucalyptus globulus Labill. in Portugal. Initial testing was done with parameter values from Australia using climate, biometric, and soils data from an irrigation and fertilization trial and a spacing trial. The model provided good estimates for stem mass and basal area, poor estimates for leaf mass, and reasonable estimates for volume. The fit between simulated and observed values was then improved by tuning parameter values to produce a final set. The calibrated model was tested, and performed well, against data from permanent sample plots (PSPs) at different locations across Portugal. Volume and basal area predictions made by 3-PG for PSPs were then compared with predictions made by the empirical model in use for E. globulus plantations in Portugal. Differences were negligible. Model outputs with the Australian parameter set and the optimum set for Portugal indicated that partitioning of carbohydrates (net primary productivity) was very different in E. globulus grown in Portugal and Australia. The study has confirmed the potential of this process-based model as a practical tool to support forest management decision-making.
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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 | 0.001 | 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".