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Record W604867780

Fisheries Challenges Associated with Ray Gibbon Drive at Riel Pond and the Sturgeon River in St. Albert, Alberta

2008· article· en· W604867780 on OpenAlexaboutno aff
Tim Allen, Lynn Anne. Maslen, Sj Melton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsSturgeonFisheryWildlifeHabitatFish <Actinopterygii>GeographyWork (physics)Environmental scienceEcologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

Ray Gibbon Drive, west of St. Albert, Alberta, currently functions as a two lane arterial roadway constructed to alleviate local traffic congestion and provide an alternate commuting route for the residents of St. Albert. Planning took place over 30 years, prolonged primarily because of environmental concerns. Because of the project's location, site sensitivities and a long history of public interest, the City of St. Albert required an environmental assessment and several federal and provincial agencies required environmental approvals. Construction challenges included: Construction of the roadway over an abandoned landfill with the risk of leakage of leachate; the need to work in Riel Pond (which discharged to the Sturgeon River) while not releasing contaminated bottom sediments, or a non-native fish species (threespine stickleback) discovered in the Pond; scheduling all work outside the period April to July (inclusive) imposed by fish and other breeding wildlife sensitivities (which led to challenging work conditions); and the need to compensate for lost fish habitat as a result of placing piers and abutments in the Sturgeon River. The road opened for traffic in 2007 with achievement of all environmental protection measures despite the numerous challenges.

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)0.001
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 score0.139
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.178
Teacher spread0.166 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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