Differences in stem taper of black alder (<i>Alnus glutinosa</i> subsp. <i>barbata</i>) by origin
Bibliographic record
Abstract
Black alder (Alnus glutinosa subsp. barbata (C.A. Mey.) Yalt.) is an important tree species in Turkey both economically and ecologically. Accurate taper and volume equations are required by most inventory systems to estimate upper stem diameter, form, and tree volume. Stem analysis data were used to examine the differences in taper and volume of black alder trees grown in naturally regenerated, plantation, and coppice stands. Statistically significant differences were observed in taper and volume of black alder trees grown in stands from these three origins. Error in total stem volume inside bark was the greatest when the taper model was fitted to plantation data and applied to seed data compared with the model fitted to coppice data and applied to seed data. Therefore, to accurately predict upper stem diameter and total or merchantable stem volume, in addition to selecting species-specific taper models, forest managers should consider the origin of the model-fitting data when choosing an appropriate taper model for their stands.
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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 | 0.001 |
| 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".