Bibliographic record
Abstract
Ecophysiological and dendroecological data from a temperate sessile oak (Quercus petraea (Matt.) Liebl.) stand in Belgium were used to develop and parameterize a dendroecological process-based model. The purpose of this model is to serve as a tool for exploring the relationship between climate variability and tree growth based on dendro ecological data. When parameterized, the model was able to correctly simulate measurements of bud-burst date, through fall (r2 = 0.95), soil water content (r2 = 0.81), transpiration (r2 = 0.80), and ring-width series from 1960 to 1999 (r2 = 0.46). Model sensitivity analysis showed that atmospheric vapor pressure deficit is the major controlling factor of transpiration in this type of ecosystem. The model shows that bole increment is principally controlled by temperature because it affects the phenological process of bud burst and thus the growing season length. Precipitation variability does not affect variation of transpiration rate and bole increment because calculated soil water stress is negligible during the simulation period. Discrepancies between observed and simulated bole increment may be a consequence of stand density variations and worm defoliation in the spring. The MAIDEN model is particularly suited for dendreocological analysis because it takes simple species, site condition, and climatic variables as input.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".