Relationships between climate and double rings in <i>Quercus ilex</i> from northeast Spain
Bibliographic record
Abstract
The influence of climatic factors on tree-ring width and the formation of double rings was studied in Quercus ilex L. growing in a coppice stand left unmanaged for 22 years. Ten trees were felled and discs were taken every 30 cm from bole and dominant branches. Dendrometer bands were installed on 10 nearby trees and the data recorded were used to confirm the accuracy of our tree-ring identification. They were also used to relate the seasonal radial growth pattern to double-ring formation. Double rings were frequent and occurred consistently along the stem. Two types of double rings could be recognized according to their width: type I, with the extra growth band accounting for approximately 50% of the tree ring; and type II, with a narrow extra growth band. Type I double rings were formed when approximately 1/2 of the growing-season precipitation occurred during the second growth period of the season and after the summer drought. Type II double rings occurred when approximately 1/3 of the precipitation in the growing season occurred after the summer drought. The formation of double rings was triggered by rainfall in summer and the extra growth-band width was related to summer and autumn environmental conditions. Double rings in Q. ilex can potentially be used in dendroclimatological studies, as they are formed in response to climatic conditions within the growing season.
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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 | 0.000 |
| 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) | 0.001 | 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".