Using Noble Gas Measurements to Derive Air‐Sea Process Information and Predict Physical Gas Saturations
Bibliographic record
Abstract
Abstract Dissolved gas distributions are important because they influence oceanic habitats and Earth's climate, yet competing controls by biology and physics make gas distributions challenging to predict. Bubble‐mediated gas exchange, temperature change, and varying atmospheric pressure all push gases away from equilibrium. Here we use new noble gas measurements from the Labrador Sea to demonstrate a technique to quantify physical processes. Our analysis shows that water‐mass formation can be represented by a quasi steady state in which bubble fluxes and cooling push gases away from equilibrium balanced by diffusive gas exchange forcing gases toward equilibrium. We quantify the rates of these physical processes from our measurements, allowing direct comparison to gas exchange parameterizations, and predict the physically driven saturation of other gases. This technique produces predictions that reasonably match N2/Ar observations and demonstrates that physical processes should force SF6 to be ∼6% more supersaturated than CFC‐11 and CFC‐12, impacting ventilation age calculations.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".