Individual variability in the movement behaviour of juvenile Atlantic salmon
Bibliographic record
Abstract
Stream-dwelling salmonid populations are generally thought to be composed of both relatively mobile and sedentary individuals, but this conclusion is primarily based on results obtained from recapture methods with low temporal resolution. In this study, the mobility of 50 juvenile Atlantic salmon (Salmo salar) was monitored using a large array of passive integrated transponder antennas buried in the bed of a natural stream. Fish locations were recorded at a high frequency for a period of 3 months in a 65 m reach. Four types of daily behaviour were identified: stationary (detected primarily at one location), sedentary (limited movement between a few locations), floater (frequent movements in a restricted home range), and wanderer (movements across the reach). Most individuals exhibited low mobility on most days, but also showed occasional bouts of high mobility. Between-individual variability accounted for only 12%–17% of the variability in the mobility data. High mobility was more frequent at low flow, but no difference was observed between the summer (12–18 °C) and the autumn (4–12 °C). Individual variation on a daily basis suggested that movement behaviour is a response to changing environmental conditions rather than an individual behavioural trait.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".