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Record W4403666385 · doi:10.1139/cjfas-2024-0100

A typology of potential hydraulic barriers to adult salmon migration in a bedrock river

2024· article· en· W4403666385 on OpenAlexafffundvenue
Morgan Wright, Max Hurson, Kendra A. Robinson, David A. Patterson, Jeremy G. Venditti

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans CanadaSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBedrockTypologyFisheryGeologyHydrology (agriculture)Environmental scienceGeographyBiologyGeomorphologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Adult Pacific salmon ( Oncorhynchus spp.) in the Fraser River, British Columbia, can die trying to retrace and ascend the river network to their natal spawning grounds due to hydraulic barriers, where encounter velocities exceed swim speeds of adult salmon. We evaluated river hydraulics, river morphology, and swimming ability to better understand these potential hydraulic barriers. A 375 km centreline velocity survey of the Fraser Canyon identified 22 high velocity locations where the distribution of velocity within the reach could produce a hydraulic barrier. We identified and studied three flow types associated with these 22 high velocity locations: (1) plunging flows, (2) rapids, and (3) overfalls, using drone footage at various discharges to examine flow structure and compare surface velocities with swimming modes. Complex flow within the major hydraulic features highlights the spatial locations requiring anaerobic swimming and areas of potential recovery that change with discharge. This approach can be used to improve the understanding of fish migration limits in a natural river system and aid in future mitigation.

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)0.001
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 score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.201
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 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

Citations1
Published2024
Admission routes3
Has abstractyes

Explore more

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