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Record W2146793851 · doi:10.1139/f08-149

Process-based modelling of decadal trends in growth, survival, and smolting of wild salmon (Salmo salar) parr in a Scottish upland stream

2008· article· en· W2146793851 on OpenAlexvenueno aff
William S. C. Gurney, P. J. Bacon, Graham Tyldesley, A. F. Youngson

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSalmoSmoltificationFish migrationJuvenileEnvironmental scienceFisherySalmonidaeEmigrationFish <Actinopterygii>GeographyEcologyBiology

Abstract

fetched live from OpenAlex

This paper reports a new model of the freshwater stages of an anadromous fish, at the core of which is a stochastic description of the size-at-age dynamics of a growing cohort. Emigration is assumed to require the individual to exceed a threshold size at a critical time of year, thus making the distributions of survival to, and age at, smolting emergent properties of the model. The model is applied to a long-term data set on juvenile Atlantic salmon ( Salmo salar ) in the Girnock Burn, Scotland, to understand the role played by decadal temperature trends in generating changes in smolt production and age distribution. We conclude that changes in age at smolting are compatible with causation by shifts in the temperature regime. However, the large attenuation between a dramatic fall in spawner numbers and a relatively minor diminution in total smolt production does not result from the physiological effects of temperature but is rather a result of strongly density-dependent mortality between the deposition of ova and the appearance of catchable fry the following summer.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.223
Teacher spread0.197 · 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 designSimulation or modeling
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

Citations41
Published2008
Admission routes1
Has abstractyes

Explore more

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