Variability of Surface Water <i>p</i>CO<sub>2</sub> in the Canadian Arctic Archipelago From 2010 to 2016
Bibliographic record
Abstract
Abstract This study provides 6 years of high‐resolution underway measurements of the sea surface partial pressure of CO2 (pCO2sw), sea surface temperature, and salinity across the Canadian Arctic Archipelago (CAA). Observed pCO2sw varied regionally, with the northern and central channels of the CAA undersaturated in pCO2sw (with respect to the atmosphere), while the western regions were typically saturated to supersaturated in pCO2sw. This apparent spatial variability was caused to some extent by the timing of our ship transit through the CAA, as we also found a general seasonal trend of pCO2sw being undersaturated in the early summer, followed by saturation to supersaturation in late summer, and a return to undersaturation during the autumn. Sea surface temperature was significantly correlated with pCO2sw at various locations across the CAA, but we also observed the effects of other regional processes like upwelling, primary production, riverine input, and sea ice melt. These processes are linked to each other, and hence, it is impossible to pinpoint only one dominant factor controlling pCO2sw variability in the CAA. However, we found that sea ice dominates the seasonal cycle of all these processes, thus making the timing of sea ice breakup a useful predictor of pCO2sw variability in the CAA. We calculated an average net oceanic sink of 14 mmol CO2 · m−2 · day−1 for the CAA during the summer and autumn seasons, but caution that a more rigorous budgeting approach is required to fully account for biases in dates and locations of our measurements.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".