Water Mass Transformation and Formation in the Labrador Sea
Bibliographic record
Abstract
Abstract Objectively analyzed surface hydrographic fields and NCEP–NCAR reanalysis fluxes are used to estimate water mass transformation and formation rates in the Labrador Sea, focusing on Labrador Sea Water (LSW). The authors estimate a mean long-term transformation of between 2.1 ± 0.2 and 3.9 ± 0.3 Sv (Sv ≡ 106 m3 s−1) over the years 1960–99 to water with densities greater than σ = 27.65 kg m−3, depending on the correction used for the latent and sensible heat fluxes. Mean long-term formation rates are found between 0.9 ± 0.2 and 1.7 ± 0.3 Sv for σ = 27.675 − 27.725 kg m−3 and 1.2 ± 0.2 and 2.0 ± 0.3 Sv for σ > 27.725 kg m−3. There is tremendous variability associated with these formation rates with years of strong water formation (5.7–6.6 ± 0.5–0.7 or 9.5–10.8 ± 0.7–1.1 Sv) mixed with years of little or no formation in the given density ranges. The North Atlantic Oscillation (NAO) is linked (correlation coefficient of 0.45, significant at the 99% level) with the overall formation rate for σ > 27.625 kg m−3. The observed long-term increase in net precipitation over the Labrador Sea does not seem to have had any significant effect on LSW, potentially reducing LSW transformation rates by 0.1 Sv. A reduction in surface salinity leads to formation occurring at a reduced density, but with little change in the amount of water transformed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".