Impact of diapycnal mixing on the saturation state of argon in the subtropical North Pacific
Bibliographic record
Abstract
Diapycnal mixing plays an important role in both physical and biogeochemical processes in the oceans, yet the rate of tracer mixing has not been adequately quantified. A theoretical analysis predicts that diapycnal mixing should raise the saturation state of noble gases in the thermocline, at a rate proportional to diapycnal diffusivity. We apply this theory to existing measurements of argon in the ventilated thermocline, where the increase in the saturation state should be proportional to the integrated effect of diapycnal mixing. Combining argon observations from time‐series stations in the North Pacific with freon ventilation age, we tentatively estimate the regional diapycnal diffusivity at 0.35 ± 0.21 10−4 m2s−1. Major sources of uncertainty include spatial and temporal variability and sparse sampling. These uncertainties could be significantly reduced using measurements of several noble gases in a transect from the isopycnal outcrop to the interior gyre.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".