Signal Strength In Sub-Annual Tree-Ring Chronologies from<i>Pinus ponderosa</i>In Northern New Mexico
Bibliographic record
Abstract
The creation of chronologies from intra-annual features in tree rings is increasingly utilized in dendrochronology to create season-specific climate histories, among other applications. A conifer latewood-width network has recently been developed for the southwestern United States, but considerable uncertainty remains in understanding site and species differences in signal strength and sample depth requirements. As part of the 22nd annual North American Dendroecological Fieldweek, the first Pinus ponderosa earlywood-width (EW) and latewood-width (LW) chronologies were developed for the Jemez Mountains in northern New Mexico. The aim was to extend an existing total ring-width (TW) chronology and to assess the potential for creating long LW chronologies. Analysis of chronology signal strength suggests that large sample size requirements remain a considerable hurdle for creating P. ponderosa LW chronologies longer than 400 years. At the Cat Mesa site, twenty-three sample trees were required to capture a statistically acceptable common signal in adjusted latewood (LWa), whereas only four samples were required for EW. This is significantly higher than sample depth requirements for LWa from the few other chronologies in the region where this statistic has been reported. A future priority should be to develop a conceptual guide for site and tree selection in order to maximize the potential for enhancing LW signal and for creating a robust network of multi-century LW chronologies.
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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 | 0.001 |
| 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 | 0.000 | 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".