Juvenile Salmon Migration Observations from the Hakai Institute Juvenile Salmon Program in the Discovery Islands in British Columbia, Canada in 2020
Bibliographic record
Abstract
The Hakai Institute Juvenile Salmon Program has been monitoring juvenile salmon migrations in the Discovery Islands in British Columbia, Canada since 2015 with the specific purpose to understand how ocean conditions experienced by juvenile salmon during their early marine migration impact their growth, health, and ultimately survival. This report summarizes migration timing, purse-seine catch intensity and composition, fish length and weight, sea-louse loads, and ocean temperatures observed from six years of this research and monitoring program. Migration timing for sockeye, pink, and chum was not significantly different than respective time-series averages and occurred on May 23 for sockeye, June 17 for chum, and on June 20 for pink salmon. In order of highest to smallest catch proportion seines were dominated by juvenile pink, sockeye, and chum salmon. Catch intensity (our relative abundance measurement) for chum was the lowest on record in the time series, though sockeye and pink catch intensity were nearer their time-series averages. Mean annual fork length for sockeye, pink, and chum salmon were all within the time-series average range. The abundance of pre-adult and adult Caligus clemensi sea lice was relatively high on juvenile sockeye, pink, and chum salmon in 2020 compared to previous years. The salmonid-specialist sea louse, Lepeophtheirus salmonis, had relatively high abundance on pink and chum salmon but low abundance on sockeye. May–June 30 m depth integrated ocean temperature in the northern Strait of Georgia in 2020 was 0.79 °C warmer than average for the time series (2015–2020), and the warmest observed in this time series.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".