Seasonal variability of water mass distribution in the southeastern Beaufort Sea determined by total alkalinity and <i>δ</i><sup>18</sup>O
Bibliographic record
Abstract
We examined the seasonal variability of water mass distributions in the southeastern Beaufort Sea from data collected between September 2003 and August 2004. Salinity, total alkalinity (TA) and isotopic composition ( δ 18 O) of seawater were used together as tracers of freshwater input, i.e., meteoric water and sea ice meltwater. We used an optimum multiparameter analysis to identify the different water masses, including the Mackenzie River, sea ice melt (SIM), winter polar mixed layer (PML), upper halocline water (UHW) with core salinity of 33.1 psu (Pacific origin) and Atlantic Water. Computed values of CO 2 fugacity in seawater ( f CO 2 ‐sw) show that the surface mixed layer (SML) remains mostly undersaturated (328 ± 55 μ atm, n = 552) with respect to the average atmospheric CO 2 concentration (380 ± 5 μ atm) over the study period. The influence of the Mackenzie River ( f CO 2‐SW > 500 μ atm) was relatively small in the southeastern Beaufort Sea, and significant fractions were only observed on the inner Mackenzie Shelf. The contribution of sea ice melt ( f CO 2‐SW < 300 μ atm) to the SML could reach 30% beyond the shelf break and close to the ice pack in autumn. The density of the PML increased through the winter due to cooling and brine rejection. The winter PML reached a maximum depth of 70 m in late April. The UHW ( f CO 2‐SW > 600 μ atm) was usually located between 120 and 180 m depth, but could contribute to the SML during wind‐driven upwelling events, in summer and autumn, and during brine‐driven eddies, in winter.
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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 | 0.004 | 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 | 0.001 |
| 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".