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Record W2898103884 · doi:10.1111/jfb.13846

Spawning‐strategy‐dependent diets in two North American populations of Atlantic salmon <i>Salmo salar</i>

2018· article· en· W2898103884 on OpenAlexaffabout
Brianne Kelly, Hugues P. Benoît, Gérald Chaput, Ross A. Jones, Michael Power

Bibliographic record

VenueJournal of Fish Biology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans CanadaUniversity of Waterloo
Fundersnot available
KeywordsSalmoBiologyCapelinFisheryPredationCoregonusEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The diet of repeat-spawner Atlantic salmon Salmo salar was investigated using carbon and nitrogen stable-isotope values from the outer growth band of scales, which reflect the fish's consumption and growth during their most recent marine phase. Isotope values for S. salar displaying different spawning strategies were compared between and within the Miramichi and Nashwaak Rivers, New Brunswick, Canada and a Bayesian mixing model was used to infer dietary contributions from potential prey items. Significant differences in the stable-isotope values were found among spawning strategies and between rivers, indicating differences in diet and feeding area, consistent with hypotheses. Bayesian mixing model results inferred the main prey items consumed during marine feeding by S. salar to consist of hyperiid amphipods and capelin Mallotus villosus for repeat alternate spawners from both rivers, sandlance Ammodytes sp. for repeat consecutive spawners from the Miramichi River and amphipods for repeat consecutive spawners from the Nashwaak River. These results demonstrate the diversity of feeding tactics among S. salar spawning strategies from the same river and between populations from different rivers. Accounting for differences in prey availability and the subsequent impact on S. salar diet and spawner return rates (i.e., marine survival) will facilitate the application of ecosystem-based management practices, such as ensuring that fisheries for forage species do not indirectly adversely affect S. salar return rates.

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 score0.054
Threshold uncertainty score0.107

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 studies0.0000.001
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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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

Citations7
Published2018
Admission routes2
Has abstractyes

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