Bubble (Mediated) Exchange in the Labrador Sea (BELS), Cruise No. MSM123, 24.11.2023 - 27.12.2023, Halifax, Canada - St. John's, Canada
Bibliographic record
Abstract
The Labrador Sea is a high latitude region of the ocean where open ocean deep convection and seasonal solubility and biology-driven changes occur faster than air-sea gas exchange can re-establish air-sea equilibrium. It is, consequently, one of the most intense sinks for carbon dioxide (CO2) and oxygen (O2) globally. Although it is clear that high-latitude regions are key for ocean-atmosphere transfer and sequestration in the deep ocean, our knowledge of the basic forcing mechanisms at play there remain very uncertain. Gas, momentum, and heat exchange are highly nonlinear functions of wind speed, indicating that mechanisms operating at high winds, such as bubble-mediated transfer, need to be constrained. Global change issues such as increasing temperatures, ocean acidification, and ocean deoxygenation are interlinked and in order to understand the changes in uptake, biogeochemical cycling, and feedback processes of environmentally important gases, mechanisms controlling their air-sea exchange must be understood. Bubble-mediated gas exchange is under-represented in models, in part due to a lack of mechanistic understanding and, thus, limited ability to parameterise its contribution to the overall gas flux. The overarching objective of BELS is to understand and quantify bubble-mediated gas exchange mechanisms. Special attention will be given to the forcing and parametrisation of air–sea exchange for the insoluble gas O2. We will employ range of complementary techniques to tackle the questions posed, including eddy covariance direct fluxes, continuous profiling, tracer release, noble gases, and direct bubble characterisation. By combining these techniques, we will have the major advantage of connecting bubble process understanding with comprehensive flow, gas saturation and gas flux measurements, and directly observing bubble-mediated gas uptake mechanisms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".