Wave Glider‐Based Measurements and Corrections of Near‐Surface <i>p</i> CO <sub>2</sub> Gradients in the Coastal Ocean
Bibliographic record
Abstract
Abstract Carbonate system dynamics are highly variable in coastal and shelf regions, and poor spatiotemporal measurement resolution leads to inadequate constraints for global carbon sequestration estimates. Additionally, conventional p CO 2 measurement‐based flux calculations require an assumption of homogeneity in near‐surface waters, excluding effects such as biological drivers and air‐sea disequilibrium. To quantify the effect of these drivers by capturing high resolution measurements during short‐term events, we present the deployment of a Liquid Robotics Wave Glider equipped with mirrored gas sensor suites at the surface and sub‐surface during the 2022 spring bloom on the Scotian Shelf in eastern Canada. The temporal variability in the data reveals biologically driven diurnal p CO 2 behavior that conventional low‐resolution methods may overlook. Additionally, through direct measurement of surface and sub‐surface p CO 2 levels, we demonstrate that conventional underway measurement methods systematically underestimate surface p CO 2 values in this region by 1–10 μatm, leading to flux estimation errors of up to 7%. These findings emphasize the value of high‐resolution data for determining drivers of spatial variability and question the capacity of underway lines to measure true surface p CO 2 values. By employing vehicle‐based measurement techniques, we can improve our understanding of carbon dynamics in coastal environments and refine flux estimates for accurate climate modeling and management strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".