Assessment of xylem phenology: a first attempt to verify its accuracy and precision
Bibliographic record
Abstract
This manuscript aims to evaluate the precision and accuracy of current methodology for estimating xylem phenology and tracheid production in trees. Through a simple approach, sampling at two positions on the stem of co-dominant black spruce trees in two sites of the boreal forest of Quebec, we were able to quantify variability among sites, between trees and within a tree for different variables. We demonstrated that current methodology is accurate for the estimation of the onset of xylogenesis, while the accuracy for the evaluation of the ending of xylogenesis may be improved by sampling at multiple positions on the stem. The pattern of variability in different phenological variables and cell production allowed us to advance a novel hypothesis on the shift in the importance of various drivers of xylogenesis, from factors mainly varying at the level of site (e.g., climate) at the beginning of the growing season to factors varying at the level of individual trees (e.g., possibly genetic variability) at the end of 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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".