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Record W2124968032 · doi:10.1577/m03-130.1

Relative Activity of Brook Trout and Walleyes in Response to Flow in a Regulated River

2004· article· en· W2124968032 on OpenAlexafffund
Karen J. Murchie, Karen E. Smokorowski

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans Canada
FundersOntario Innovation Trust
KeywordsSalvelinusFontinalisTroutHabitatFisheryFish <Actinopterygii>Catch and releaseEnvironmental scienceSTREAMSTelemetryInvertebrateEcologyBiology

Abstract

fetched live from OpenAlex

Abstract Coded electromyogram telemetry transmitters were used to examine the effects of varying flows on the relative activity of brook trout Salvelinus fontinalis and walleye Sander vitreus in a regulated river. The relative activity levels of two brook trout and two walleyes were continuously monitored for a minimum of 24 h, and measurements were compared with river flow values logged at nearby gauging stations. Generally, fish relative activity levels mimicked patterns of flow change, peaks in activity level corresponding to peaks in flow. Mean relative activity was generally greatest at extreme high (≥25-m3/s) and low (&amp;lt;15-m3/s) flows. High flows may have elicited hyperactivity (increased activity) as fish sought suitable refugia, increased activity to hold position in the water column, or increased feeding activity on increased levels of drifting invertebrates. Hyperactivity at low flows may have been caused by relocation due to habitat loss or ease of movement at lower flow regimes. Physiological telemetry provides researchers with a method of quantifying the immediate effects of flow changes on fish. Increasing our knowledge of the effects of river regulation on fish is essential to the development of more effective management strategies that balance ecology and economics.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.053
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

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

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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 teacher head, 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

Citations46
Published2004
Admission routes2
Has abstractyes

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