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Record W2153222372 · doi:10.1139/s03-079

New portable fishway design for existing trapezoidal weirs

2004· article· en· W2153222372 on OpenAlexvenueno aff
Youichi Yasuda, Iwao Ohtsu, Masuyuki Takahashi

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWeirFish migrationJuvenileFish <Actinopterygii>FisheryUpstream (networking)Environmental scienceHydrology (agriculture)GeologyEngineeringGeographyEcologyBiologyGeotechnical engineeringCartography

Abstract

fetched live from OpenAlex

The improvement of the weir without a fishway is required in order that diadromous fishes, shrimps, and crabs can migrate to their upstream and downstream habitats. This paper presents a proposal of a portable fishway to be set on the waterside of a trapezoidal weir and discusses the effect of the proposed fishway on the migration of diadromous aquatic animals in the trapezoidal weir. Field experiments concerning the proposed fishway were carried out at a trapezoidal weir having a slope of 26.5° (Vertical 1: Horizontal 2) and 2.0 m drop height. The field experiments revealed that the juvenile ayu fish (Plecoglossus altivelis) having a body length of 4.4–10 cm could migrate to their upstream habitats through the proposed portable fishway even if the slope of the fishway is 19°. About 120 000 juvenile ayu could migrate upstream via the fishway during 9 d. The migration route of juvenile ayu can be explained on the basis of the flow characteristics in the fishway. Measurements of the flow velocity and the air concentration distribution in the portable fishway support the conclusion that the juvenile ayu can easily migrate upstream through the fishway. Also, the proposed fishway could be helpful for the upstream migration of benthic fishes, shrimps, and crabs. Key words: fishway, migration, diadromous fish, gabion, drop structure, weir.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.197
Teacher spread0.184 · 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

Citations10
Published2004
Admission routes1
Has abstractyes

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