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Record W2558383126 · doi:10.1139/cjfas-2016-0301

The effects of riparian disturbance on the condition and summer diets of age-0 brook trout (<i>Salvelinus fontinalis</i>) in three central Appalachian streams

2016· article· en· W2558383126 on OpenAlexvenueno aff
Jered M. Studinski, Andrew W. Hafs, Jonathan M. Niles, Kyle J. Hartman

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSalvelinusFontinalisTroutRiparian zoneSTREAMSDisturbance (geology)Context (archaeology)EcologyEnvironmental scienceBiologyFisheryGeographyFish <Actinopterygii>Habitat

Abstract

fetched live from OpenAlex

Forested headwater streams are dependent on their riparian zones for many critical goods and services. It is assumed that riparian disturbance affects stream food webs, but for some ecologically and economically important taxa like brook trout (Salvelinus fontinalis), little research has been performed. This study found that intense but spatially limited riparian disturbance resulted in significant but context-dependent changes in the diets and condition of age-0 brook trout in three central Appalachian streams. Dietary shifts in two of the streams appeared to enable age-0 brook trout to maintain or increase condition following riparian tree removal. A significant relationship between fish condition and the importance of Ephemeroptera as prey was observed. The lack of dietary shift to energetically important ephemeropterans coincided with decreased fish condition within one stream previously identified to be mildly impacted by acid precipitation. The context within which riparian disturbance occurs plays an important role in determining the overall impact to age-0 brook trout and should be an important consideration in future regulatory and management decisions.

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)0.000
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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.009
GPT teacher head0.194
Teacher spread0.185 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

Explore more

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