The changing composition of the Gulf of St. Lawrence inflow waters observed from transient tracer measurements
Bibliographic record
Abstract
Abstract. The deep waters of the Gulf of St. Lawrence (GSL) have experienced a significant reduction in dissolved oxygen content during the past decades. One widely documented driver of this deoxygenation is a change in the composition of the deep inflowing water that ventilates the Gulf. This deep water is known to consist of a mix of warmer, less-oxygenated North Atlantic Central Waters (NACW) and cooler, more-oxygenated Labrador Current Waters (LCW), with prior studies inferring a shift towards increased NACW contribution. However, this compositional change has only ever been inferred indirectly from physical and biogeochemical measurements via the use of inverse methods such as water mass analysis. In this study, we present results from the first spatially-comprehensive deep water transient tracer surveys in the GSL, allowing us to directly map mean age estimates and use these to infer recent changes in the composition of regional deep waters. The results reveal an unexpected age distribution, with 'older' deep waters present near the Gulf's entrance, whereas 'younger' water is found further inshore, contrary to the expected estuarine circulation pattern, which transports deep water inland (increasing age along the flow path). This implies a gradual increase in the proportion of NACW from inshore areas towards the Gulf's entrance and provides direct evidence that the shift towards NACW dominated deep waters is ongoing as of 2022, contrary to earlier predictions of the complete disappearance of the younger, well-oxygenated LCW.
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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 | 0.000 |
| 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".