Late-Holocene NAO and oceanic forcing on high-altitude proglacial sedimentation (Lake Bramant, Western French Alps)
Bibliographic record
Abstract
Comparison of glacially derived clastic inputs in high altitude proglacial lake Bramant (Western French Alps) with measured North Atlantic Oscillation winter (NAO w ) index reveals an inverse correlation between ad 1884 and 1968 at the pluridecadal timescale (20–25 years). This reflects periodical variations in snow accumulation over Lake Bramant catchment area partly influencing the glacier mass balance in the watershed. Further comparisons with reconstructed NAO w index since ad 1500 highlight spatial and temporal variations of the pluridecadal NAO w influence on this alpine climate, especially at the end of the ‘Little Ice Age’. In addition, wavelet analysis of continuous proxies of clastic sedimentation over the last 4150 years indicates significant pluridecadal variability at frequencies compatible with the NAO (30 years), while periods centered at 60–70 years could also be linked to the North Atlantic Ocean–atmosphere internal variability (Atlantic Multidecadal Oscillation (AMO)). The influence of the North Atlantic deep water production on the regional alpine climate is also suggested by a significant 550 yr cycle of clastic inputs since 2800 cal. BP. Coupling between the North Atlantic Ocean and the atmosphere seems therefore to play a fundamental role on glacier mass balance and climate during the late Holocene in the western Alps.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".