Two MATLAB programs for computing paleo-elevations and burial ages from paired-cosmogenic nuclides
Bibliographic record
Abstract
Methods based on cosmic-ray produced nuclides are key to improve our understanding of the Earth surface dynamic. Measuring multiple cosmogenic nuclides in the same rock sample has a great potential, but data interpretation requires rigorous and often complex mathematical treatments. In order to make progress on this topic, this paper presents two easy-to-use MATLAB© programs permitting to derive information from pairs of cosmogenic nuclides ( 26 Al- 10 Be or 10 Be- 21 Ne) measured in rock samples that have been exposed to cosmic rays in the past: "Paleoaltitude.m" and "Burial.m" Codes available here as supplementary material. •"Paleoaltitude.m" computes paleoelevations from a sample whose burial age is known. This new paleoaltimetry method is presented in detail in Blard et al. [1]. The present article also develops the mathematical approach. •Since the elevation of exposure may affect the accuracy of a burial age [1], the second MATLAB© script "Burial.m" is designed to compute burial ages from 26 Al- 10 Be or 10 Be- 21 Ne pairs, taking into account the position of a sample (elevation and latitude) during its preburial exposure history.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.051 | 0.020 |
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".