A Study On Dendroclimatic Potential Of Chir Pine (Pinus Roxburghii) Grown In Bahali District Mansehra Kp Pakistan
Bibliographic record
Abstract
This study is carried out to evaluate the dendro-climatic potential of Chir pine (Pinus roxburghi) growing under the moist temperate condition of Bahali forest area of Khyber Pakhtunkhwa. For this purpose, wood material in the form of tree cores was extracted from healthy trees randomly. The cores were prepared for data measurement using standard laboratory procedures. Data regarding Total Ring Width (TRW) were measured with the help Win-Dendro System. The collected data were compiled and analyzed statistically using computer-based software Cofecha and R packages. Results showed that an increase of 309.3 mm in total annual precipitation and 0.426 C. This species reflected accepted mean sensitivity value (0.297) under these climatic conditions. The climate-growth relationship for 56 years (1965-2021) revealed that precipitation is acting as a limiting factor for the growth of this species and temperature is playing its optimum role. It was concluded that Chir Pine has tremendous dendro-climatic potential which is an indication that environmental changes had created impression on growth and developmental of the trees in the study area. Further, it is recommended that this species can be used for further research concerning, reconstruction of climatic parameters and other future issues of climate changes, but long-term chronology development is prerequisite
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".