Spatial and temporal distributions of surface mass balance between Concordia and Vostok stations, Antarctica, from combined radar and ice core data: first results and detailed error analysis
Bibliographic record
Abstract
Abstract. Results from ground-penetrating radar (GPR) measurements and shallow ice cores carried out during a scientific traverse between Dome Concordia (DC) and Vostok stations are presented in order to infer both spatial and temporal characteristics of snow accumulation over the East Antarctic Plateau. Spatially continuous accumulation rates along the traverse are computed from the identification of three equally spaced radar reflections spanning about the last 600 years. Accurate dating of these internal reflection horizons (IRHs) is obtained from a depth–age relationship derived from volcanic horizons and bomb testing fallouts on a DC ice core and shows a very good consistency when tested against extra ice cores drilled along the radar profile. Accumulation rates are then inferred by accounting for density profiles down to each IRH. For the latter purpose, a careful error analysis showed that using a single and more accurate density profile along a DC core provided more reliable results than trying to include the potential spatial variability in density from extra (but less accurate) ice cores distributed along the profile. The most striking feature is an accumulation pattern that remains constant through time with persistent gradients such as a marked decrease from 26 mm w.e. yr−1 at DC to 20 mm w.e. yr−1 at the south-west end of the profile over the last 234 years on average (with a similar decrease from 25 to 19 mm w.e. yr−1 over the last 592 years). As for the time dependency, despite an overall consistency with similar measurements carried out along the main East Antarctic divides, interpreting possible trends remains difficult. Indeed, error bars in our measurements are still too large to unambiguously infer an apparent time increase in accumulation rate. For the proposed absolute values, maximum margins of error are in the range 4 mm w.e. yr−1 (last 234 years) to 2 mm w.e. yr−1 (last 592 years), a decrease with depth mainly resulting from the time-averaging when computing accumulation rates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".