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Record W2647161634 · doi:10.1080/24705357.2017.1288555

The effects of horizontally and vertically oriented baffles on flow structure and ascent performance of upstream-migrating fish

2017· article· en· W2647161634 on OpenAlexafffund
Eva C. Enders, Theodore Castro‐Santos, Jay Lacey

Bibliographic record

VenueJournal of Ecohydraulics · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversité de SherbrookeFisheries and Oceans Canada
FundersU.S. Geological SurveyNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsBaffleUpstream (networking)Fish <Actinopterygii>Marine engineeringFlow (mathematics)FisheryGeologyMechanicsEnvironmental scienceComputer scienceEngineeringMechanical engineeringPhysicsBiologyTelecommunications

Abstract

fetched live from OpenAlex

Considerable effort has been expended to construct culverts and fishways that allow for fish passage. However, the designs have seldom considered behaviour, energetics, and biomechanics of fish. In this study, we performed controlled experiments, in which upstream-migrating Alewife (Alosa pseudoharengus) and Brook Trout (Salvelinus fontinalis) were allowed to volitionally enter either one of two open channels. These channels were outfitted with horizontally and vertically oriented baffles. The flow structure was characterized using acoustic Doppler velocimeter measurements. The added baffles had a marked influence on the flow field, which was distinct between horizontal and vertical baffles, indicative of horizontally and vertically orientated vortices, respectively. Passage success was measured, both in terms of attraction and ascent performance under each flow condition. The results indicated that Alewife and Brook Trout staged significantly more attempts into the vertical baffled channel compared to the horizontal baffled channel. However, Alewife traversed greater distances swimming in the channel with the horizontal baffles at the lower flow condition. Brook Trout also swam further under low flow but traversed similar dtistances in both channels. This information furthers our understanding of both ascent performance and behavioural responses of fish in relation to turbulent flow and roughness orientation.

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 score0.022
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

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

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 head0.003
GPT teacher head0.199
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

Citations35
Published2017
Admission routes2
Has abstractyes

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