Traitement et production d'une série dendroisotopique millénaire
Bibliographic record
Abstract
The stable isotopic ratios of carbon and oxygen in tree rings are remarkable paleoclimatic data. In northeastern Canada, where climatic reconstructions longer than 500 years are very rare and where none is based on tree-ring isotopes, subfossil stems from boreal lakes can be used to produce long isotopic series. The most important steps in producing millennial isotopic series consist in selecting the material to study (lakes, living trees, subfossil stems) and the method to sample tree rings in order to obtain a climate reconstruction of high temporal resolution. The climatic significance of the isotopic ratios was determined by correlations with climatic parameters, and validated by our understanding of the physiological and pedogeochemical response mechanisms. The significant correlation obtained for the delta-18O series with summer maximal temperature has allowed reconstructing the mean of June-July maximum temperature over the last millennium by using subfossil stems recovered from a boreal lake. This new millennial series, the first isotopic series in northeastern Canada, is one of the first in the world to use delta-18O values as a proxy for climate. It brings new knowledge of the past climate for northeastern Quebec by highlighting that the medieval warm anomaly (1000-1250 AD) was as warm as the last three decades and the warming observed since 1970 is one of the most important of the last millennium.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".