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Loss of Fish Habitat as a Consequence of Inappropriately Constructed Stream Crossings

2005· article· en· W1983662331 on OpenAlexaffabout
R. J. Gibson, Richard L. Haedrich, C. Michael Wernerheim

Bibliographic record

VenueFisheries · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMemorial University of Newfoundland
FundersVlaamse regering
KeywordsCulvertHabitatFish <Actinopterygii>SalmoFisherySTREAMSIndigenousDiversity of fishTruckGeographyEnvironmental scienceEnvironmental protectionEcologyEngineeringBiology

Abstract

fetched live from OpenAlex

In the light of declines in Atlantic salmon (Salmo salar) stocks, we sought to determine the extent to which stream crossings along a newly constructed section of the Trans Labrador Highway (TLH Phase II) in southern Labrador accorded with government regulations for fish habitat protection. We surveyed crossings of permanent streams over a 210 km road segment, containing 4 bridges and 47 culverts. Fifty-three percent of culverts posed problems to fish passage, due to poor design or poor installation. We conjecture that cost and inadequate environmental oversight in the field explain the weak compliance with the relevant fisheries guidelines. Our research has prompted the federal regulator to instigate remediation of problems with the Phase II part of the highway. In addition many of the planned stream crossings for Phase III of the TLH were re-designed, and a commitment to careful monitoring of the installations has been made by the federal regulator in cooperation with the indigenous inhabitants.

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)0.004
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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

Citations171
Published2005
Admission routes2
Has abstractyes

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