Holocene history of Rio Tranquilo Glacier, Monte San Lorenzo (47°S), Central Patagonia
Bibliographic record
Abstract
A well-resolved glacial chronology is crucial to compare sequences of glacial/climate events within and between regions, and thus, to unravel mechanisms underlying past climate changes. Important efforts have been made towards understanding the Holocene climate evolution of the Southern Andes; however, the timing, patterns and causes of glacial fluctuations during this period remain elusive. Advances in surface exposure dating techniques, together with the establishment of a Patagonian 10Be production rate, have opened new possibilities for establishing high-resolution glacial chronologies at centennial/decadal scale. Here we present a new comprehensive Holocene moraine chronology from Mt. San Lorenzo (47°S) in central Patagonia, Southern Hemisphere. Twenty-four new 10Be ages, together with three published ages, indicate that the Río Tranquilo glacier approached its Holocene maximum position sometime, or possibly on multiple occasions, between 9860 ± 180 and 6730 ± 130 yr. This event(s) was followed by a sequence of slightly smaller advances at 5750 ± 220, 4290 ± 100 (?), 3490 ± 140, 1440 ± 60, between 670 ± 20 and 430 ± 20, and at 390 ± 10 yr ago. By comparing our results with other glacier chronologies from central and southern Patagonia, we explore the role of the Southern Westerly Winds as a pacemaker of the Holocene glacier fluctuation in southern South America.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".