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Record W2077741415 · doi:10.1577/m07-036.1

An Efficient Smolt Trap for Sandy and Debris-Laden Streams

2007· article· en· W2077741415 on OpenAlexfundno aff
Justin G. Scace, Benjamin H. Letcher, John Noreika

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersMcMaster University
KeywordsWeirTripod (photography)Trap (plumbing)FlumeEnvironmental scienceSTREAMSDebrisHydrology (agriculture)CanyonMarine engineeringGeologyComputer scienceEngineeringGeotechnical engineeringEnvironmental engineeringFlow (mathematics)OceanographyMechanical engineeringGeographyMathematics

Abstract

fetched live from OpenAlex

Abstract Tripod weir and box traps are traditionally used to capture and enumerate out-migrating salmonid smolts in short-term studies and in streams where temporary or portable traps are the only practical option. Although traditional traps can be effective when conditions are ideal, they are often unable to withstand high-discharge events in streams containing a large amount of debris or sandy substrates. We created a rotary-screw trap and resistance board weir hybrid design that we evaluated along with a tripod weir and box trap, both in a 6.1-m-wide flume and in the field. The new design outperformed the tripod weir in both situations. The tripod weir failed in 10 min in the flume trial, whereas the new design was still operating at the conclusion of an 8-h trial under the same conditions. The new design operated continuously in the field during a high-discharge event that caused the tripod weir to fail. The new design also required less frequent cleaning than the tripod weir. The trap efficiency of the new design was estimated by using passive integrated transponder (PIT) tag antennas and radiotelemetry. The trap was 80% efficient (n = 40) in capturing migrating PIT-tagged individuals detected at an antenna upstream of the trap and 87.5% efficient (n = 48) at recapturing fish that had been tagged and released upstream. With its high efficiency and increased resiliency over the tripod weir, the new trap design will benefit management and research efforts in streams where traditional traps are unsuitable.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.220
Teacher spread0.214 · 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 designBench or experimental
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

Citations8
Published2007
Admission routes1
Has abstractyes

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