Climatology of Transport in the Strait of Belle Isle
Bibliographic record
Abstract
Abstract The Strait of Belle Isle (SBI) is an important pathway for water mass exchanges between the Labrador Shelf and the Gulf of St. Lawrence (GSL), particularly for transport toward the GSL. Seasonal and inter‐annual variability of transport in the SBI are examined using 15 years of moored acoustic Doppler current profiler data. Tidal currents are largely along strait and homogeneous with depth. Transports are toward the GSL on average, lowest (−1.0 ± 0.8 dSv) from April to July, and highest (−4.0 ± 1.1 dSv) from September to January. Averaged seasonal transports are usually within one standard deviation of previously published modeled values. The volume of winter Labrador Shelf water (LShW) entering the GSL is computed by transport integration and compares well with integrated volumes that meet LShW temperature‐salinity criteria during an annual March survey of the GSL. Integrating over the whole year showed that on average 649 ± 397 km 3 enters the GSL after the March surveys are conducted, independently of the volume that has entered up to March; this addition represents on average about a third of the total volume. Annual volumes of LShW calculated from transport suggest that flow through the SBI accounts for 12%–18% of the GSL winter surface mixed layer. Cross‐strait current shear may affect transport integration values, but sea surface temperature data suggests this bias is limited to the summer. Corrections are empirically derived to account for cross‐strait shear in our transport calculation. The corrected time series suggests that the average transport may be flowing toward the Labrador Shelf in July (0.6 ± 1.0 CI [0.1 1.1] dSv).
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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) | 0.002 | 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".