MétaCan
Menu
← Back to cohort
Record W2033199294 · doi:10.1139/cjfas-2012-0525

State-dependent migratory timing of postspawned Atlantic salmon (<i>Salmo salar</i>)

2013· article· en· W2033199294 on OpenAlexvenueno aff
Elina Halttunen, Jenny L. A. Jensen, Tor F. Næsje, Jan Grimsrud Davidsen, Eva B. Thorstad, Cedar M. Chittenden, Sandra Hamel, Raul Primicerio, Audun H. Rikardsen

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSalmoOverwinteringFisheryHabitatBiologySalmonidaeSexual maturityFish migrationEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Atlantic salmon (Salmo salar) often survive spawning and migrate back to the sea to feed, either shortly after spawning in autumn or the following spring. We conducted a 4-year observational field study using telemetry to evaluate the determinants of migration timing in Atlantic salmon postspawners (kelts). We found that individuals with low energy reserves migrated early to the risky but productive marine habitat, whereas individuals with greater energy reserves stayed in the safe but less productive river habitat until staying became energetically more costly than migrating. For males, the likelihood of overwintering in the river instead of migrating in autumn increased 27-fold with each increase in body condition index, whereas almost all females overwintered in the river. Among spring migrants, body condition was the strongest determinant of migration timing, and females left the river about 5 days later than males. Our study suggests that migration timing in Atlantic salmon kelts is the outcome of adaptive state-dependent habitat use, related to individual and sexual differences in energy allocation during spawning.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.200
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations42
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→