Modelling the dispersal of herring and hake larvae in the Strait of Georgia for the period 2007–2009
Bibliographic record
Abstract
Abstract The Strait of Georgia (SoG), between Vancouver Island and mainland British Columbia, is a larval rearing ground for both hake and herring stocks, which are commercially important. Year‐to‐year variability in larval retention within the strait is examined by simulating drift tracks of larvae for these species using an ocean circulation model and a particle‐tracking model. Larvae with different vertical swimming behaviors were tracked in the springs of 2007, 2008, and 2009. Since herring larvae mostly stay near the surface, their distribution is heavily influenced by the wind. Strong winds to the north soon after the hatching period tend to wash herring larvae out of SoG and winds to the south help retain herring larvae inside the Strait. In 2007, the model indicates a massive wind‐driven export of herring larvae which may have led to the observed failure of herring production. In contrast, hake larvae reside deeper in the water column (50–200 m). Their distribution is less sensitive to surface forcing but is shaped by a deep gyre with cross‐strait currents. This study also suggests that the northern and southern SoG are weakly connected for herring larvae dispersal, which makes both regions potentially important to recruitment.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".