Impact of accumulation rate on firn core water isotopic records from a same region of Adelie Land with high katabatic winds
Bibliographic record
Abstract
Whereas water isotopic records from polar deep ice cores can be interpreted at first order in terms of site temperature, the isotopic signature recorded in shallow cores from Adelie Land (coastal East Antarctica) is less straightforward to decipher (Goursaud et al. 2017, 2019; Leroy-Dos Santos, PhD 2021, 2023). The origin of moist air masses bringing precipitation, the influence of blowing snow, redistribution or sublimation strongly imprint the isotopic signal recorded in firn cores of this region where katabatic winds blow hard. Nonetheless these firn archives are our best way to reconstruct the recent past climatic trend and variability in this area where meteorological monitoring is very sparse and recent. In this study we compare the water isotopic profiles from firn cores (20 to 70m deep) drilled only a few kilometers apart, in the so-called “D47” area, about 150km inland from Dumont d’Urville at an altitude of 1500m. This site is characterized by very strong katabatic winds and mean accumulation rates can locally vary by several tens of percent. We can thus investigate the effect of very locally different deposition conditions on the isotopic records while the recorded regional climate is the same.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".