Les séries dendroisotopiques et leur signification climatique
Bibliographic record
Abstract
Three carbon and oxygen dendroisotopic series representative of the upstream sector of the La Grande River watershed and covering the period between 1800 and 2005 were produced under the ARCHIVES project. In order to use tree-ring isotopic ratios to reconstruct climatic conditions of the last centuries, we first assessed their climatic significance by conducting a statistical study of their relationship with hydrometeorological series available for the region. The results show that the two types of isotopic ratios in wood cellulose (delta-13C and delta-18O) are generally sensitive to the same climatic parameters, but at varying degrees, and that this sensitivity increases when the two isotopic indicators are combined (mean delta-13C and delta-18O values). They respond to the maximum temperature and total precipitation of the summer season (June to August), and also to some parameters integrating several aspects of the regional climate such as a climate index combining temperatures and precipitations, the vapor pressure deficit (VPD) and regional River discharge. VPD is the parameter that most strongly correlates with the isotopic values, due to its direct influence on isotope fractionation processes related to stomatal functioning. The results presented in this chapter, clearly show that isotopic ratios of black spruce trees can be considered as excellent climate indicators for the boreal sector of northeastern America.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".