Significant overestimation of needle surface area estimates based on needle dimensions in Scots pine (<i>Pinus sylvestris</i>)
Bibliographic record
Abstract
Needle length and width at midpoint are often used to make estimates of needle surface area for conifers. For these estimates, Scots pine (Pinus sylvestris L.) fascicles are assumed to be cylindrical; thus, for a two-needle pine, the cross section of a needle within the fascicle is assumed to be hemicylindrical. The objectives of this study were to determine whether these assumptions lead to a good estimate of the actual surface area and how needles vary with tree age and crown position. We used a digital scanning microscope to measure needle width, thickness, and perimeter at 11 positions along 28 needles from different crown positions in different-aged trees and found that they varied with position within the individual needle as well as with tree age and crown position. Needle shape was relatively constant: needle width and perimeter both increased from the base to the needle midpoint and then decreased slightly to the needle tip, but needles were not hemicylindrical and actual perimeters were nearly 12% larger than predicted perimeters. The predicted surface areas based on measurements of width at the needle midpoint and length need to be reduced by 9% to account for the fact that needles taper and are not cylindrical. Furthermore, tree age and crown position must be considered when crown-level estimates are made.Key words: digital image analyzer, light microscope, needle width, needle thickness, needle perimeter, Pinus sylvestris.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".