Climatic response of<i>Cedrus deodara</i>tree-ring parameters from two sites in the western Himalaya
Bibliographic record
Abstract
Cores of Cedrus deodara D. Don from two different sites of western Himalaya were subjected to densitometric analysis to obtain data for earlywood, latewood, minimum, maximum, and mean densities and total ring width. Most of these variables show moderately high values of common variance and signal to noise ratio except latewood and maximum densities. These analyses suggest density parameters of this species may be useful in dendro climatic studies. Response function analyses indicate significant relationships between pre-monsoon (March-April-May) summer climate and earlywood density parameters, as well as total ring width. Based on the relationships derived from response function analyses, the potential of tree-ring chronologies from this species to provide reconstructions of the pre-monsoon climate in western Himalayan region has been established.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".