Energetics and morphology of sockeye salmon: effects of upriver migratory distance and elevation
Bibliographic record
Abstract
Depending on population, wild Fraser River sockeye salmon Oncorhynchus nerka travel distances of <100 km to >1100 km and ascend elevations ranging from near sea‐level to 1200 m to reach spawning areas. Populations embarking on distant, high elevation migrations ( i.e . Early Stuart, Chilko and Horsefly populations) began their upriver spawning migrations with higher densities of somatic energy ( c . 9·2 to 9·8 MJ kg −1 ) and fewer eggs ( c . 3200 to 3800) than populations making shorter, low elevation migrations ( i.e . Weaver and Adams; c . 7·1 to 8·3 MJ kg −1 gross somatic energy and c . 4300 to 4700 eggs). Populations making difficult upriver migrations also had morphologies that were smaller and more fusiform than populations making less difficult migrations, traits that may facilitate somatic energy conservation by reducing transport costs. Indeed, fish travelling long distances expended less somatic energy per unit of migratory difficulty than those travelling shorter distances (2·8 to 3·8 kJ v . 10–1400 kJ). Consistent with evolutionary theory, difficult migrations appear to select for energy efficiency but ultimately fish making more difficult migrations produce fewer eggs, even when differences in body length have been accounted for. Despite large among‐population differences in somatic energy at the start of upriver migration, all populations completed migration and spawning, and subsequently died, with c . 4 MJ kg −1 of energy remaining, a level which may reflect a threshold to sustain life.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".