(Table 1) Stable oxygen and carbon isotopic ratios of tree rings, and tree ring width of white spruce (Picea glauca), Ennadai Lake
Bibliographic record
Abstract
Stable isotope ratios from tree rings and peatland mosses have become important proxies of past climate variations. We here compare recent stable carbon and oxygen isotope ratios in cellulose of tree rings from white spruce (Picea glauca), growing near the arctic tree line; and cellulose of Sphagnum fuscum stems, growing in a hummock of a subarctic peatland, in west-central Canada. Results show that carbon isotopes in S. fuscum correlate significantly with July temperatures over the past ~20 yr. The oxygen isotopes correlate with both summer temperature and precipitation. Analyses of the tree-ring isotopes revealed summer temperatures to be the main controlling factor for carbon isotope variations, whereas tree-ring oxygen isotope ratios are controlled by a combination of spring temperatures and precipitation totals. We also explore the potential of combining high-frequency (annual) climate signals derived from long tree-ring series with low-frequency (decadal to centennial) climate signals derived from the moss remains in peat deposits. This cross-archive comparison revealed no association between the oxygen isotopes, which likely results from the varying sensitivity of the archives to different seasons. For the carbon isotopes, common variance could be achieved through adjustments of the Sphagnum age model within dating error.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.011 |
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".