A zero-exposure time test on an erratic boulder: evaluating the problem of pre-exposure in Surface Exposure Dating
Bibliographic record
Abstract
Abstract. The method of surface exposure dating using in-situ produced cosmogenic nuclides has become an important and widely applied tool in Quaternary science. One application is the dating of erratic boulders on moraines. An important problem however remains: the evaluation of potential pre-exposure time for samples from boulder surfaces. We have tested pre-exposure by sampling all sides of a recently exposed boulder in order to measure inherited nuclides from prior exposure periods. The sampled erratic boulder rests on the right lateral moraine of the most recent advance of the Glacier de Tsijiore Nouve in the Arolla Valley, Switzerland. Mapping of the area was done to reconstruct the Holocene fluctuations of the glacier. This glacier is especially useful for such a test as it is characterized by an ideal geometric relationship between accumulation and ablation area and, therefore, responds rapidly to mass-balance changes. The sampled boulder was deposited in 1991. Assuming no prior exposure the expected concentration of a given cosmogenic nuclide should be near zero. The 10Be/9Be ratios of the five measured samples were indistinguishable from blank values within the given errors, demonstrating that the samples did not experience pre-exposure. Three samples measured for 21Ne reveal 21Ne/20Ne and 22Ne/20Ne ratios similar to those of air, with no detectable prior cosmogenic Ne accumulation.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".