In situ cosmogenic radiocarbon production and 2‐D ice flow line modeling for an Antarctic blue ice area
Bibliographic record
Abstract
Radiocarbon measurements at ice margin sites and blue ice areas can potentially be used for ice dating, ablation rate estimates and paleoclimatic reconstructions. Part of the measured signal comes from in situ cosmogenic 14C production in ice, and this component must be well understood before useful information can be extracted from 14C data. We combine cosmic ray scaling and production estimates with a two‐dimensional ice flow line model to study cosmogenic 14C production at Taylor Glacier, Antarctica. We find (1) that 14C production through thermal neutron capture by nitrogen in air bubbles is negligible; (2) that including ice flow patterns caused by basal topography can lead to a surface 14C activity that differs by up to 25% from the activity calculated using an ablation‐only approximation, which is used in all prior work; and (3) that at high ablation margin sites, solar modulation of the cosmic ray flux may change the strength of the dominant spallogenic production by up to 10%. As part of this effort we model two‐dimensional ice flow along the central flow line of Taylor Glacier. We present two methods for parameterizing vertical strain rates, and assess which method is more reliable for Taylor Glacier. Finally, we present a sensitivity study from which we conclude that uncertainties in published cosmogenic production rates are the largest source of potential error. The results presented here can inform ongoing and future 14C and ice flow studies at ice margin sites, including important paleoclimatic applications such as the reconstruction of paleoatmospheric 14C content of methane.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".