South Pole glacial climate reconstruction from multi-borehole laser particulate stratigraphy
Bibliographic record
Abstract
Abstract The IceCube Neutrino Observatory and its prototype, AMANDA, were built in South Pole ice, using powerful hot-water drills to cleanly bore > 100 holes to depths up to 2500 m. The construction of these particle physics detectors provided a unique opportunity to examine the deep ice sheet using a variety of novel techniques. We made high-resolution particulate profiles with a laser dust logger in eight of the boreholes during detector commissioning between 2004 and 2010. The South Pole laser logs are among the most clearly resolved measurements of Antarctic dust strata during the last glacial period and can be used to reconstruct paleoclimate records in exceptional detail. Here we use manual and algorithmic matching to synthesize our South Pole measurements with ice-core and logging data from Dome C, East Antarctica. We derive impurity concentration, precision chronology, annual-layer thickness, local spatial variability, and identify several widespread volcanic ash depositions useful for dating. We also examine the interval around ∼74 ka recently isolated with radiometric dating to bracket the Toba (Sumatra) supereruption.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; both teacher heads agree on what is shown here.
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".