Geoscience of Climate and Energy 6. Tree Rings as Temperature Proxies
Bibliographic record
Abstract
Tree rings have provided annually resolved and precisely dated proxy climate records for large areas of the earth’s land surface. These records are considerably longer than instrumental climate data and allow the reconstruction of climate history, trends and patterns over a wide range of temporal and spatial scales. This paper briefly reviews the principles and assumptions that underlie the reconstruction of temperatures from tree-ring data, and provides three examples of their application at differing spatial and temporal scales over the last millennium. SOMMAIRE Les anneaux de croissance des arbres ont permis d’expliquer et de dater avec precision, bien qu’indirectement, des evenements climatiques portant sur de grandes etendues de la surface terrestre. La portee temporelle de ces archives naturelles depasse de beau-coup celle de tout registre climatique d’instruments humains et permet de reconstituer l’histoire, les tendances et patrons climatiques pour une gamme etendue d’echelles dans le temps et l’e-space. Le present article presente une revue sommaire des principes et postulats qui fondent la reconstitution des conditions meteorologiques a partir des donnees des anneaux de croissance des arbres, ainsi que trois exemples d’application pour differentes echelles temporelles et spatiales au cours du dernier millenaire.
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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 | 0.002 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".