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Record W6981456584

Elaho River Salmon Restoration Project

2022· article· en· W6981456584 on OpenAlexaboutno aff

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicData Analysis and Archiving
Canadian institutionsnot available
Fundersnot available
KeywordsChinook windFish migrationOncorhynchusWatershedHatcherySound (geography)Juvenile
DOInot available

Abstract

fetched live from OpenAlex

The focus of this project has been to remove several house sized boulders that created an anadromous barrier in the upper Elaho River, a traditional Chinook salmon river. The project was developed in partnership with Squamish Nation and Fisheries and Oceans Canada in order to modify the barriers to restore Chinook salmon access to over 50km of upstream river habitat. Historically, Squamish Nation had summer camps in the upper Elaho River watershed to harvest Chinook salmon but after the construction of the Elaho Logging Road in the early 1970s the river was narrowed and large boulders resulted in an anadromous barrier. Over the past 5 years the Squamish River Watershed Society has been removing the boulder obstructions and working with the local Tenderfoot Hatchery to release juvenile Chinook salmon into the upper watershed. In order to assess the effectiveness of the restoration efforts a rigorous fisheries monitoring program was initiated to establish base-line data and then to follow-up post-restoration. The monitoring program included physical observations of juvenile salmonids through electofishing techniques as well as collecting water samples for eDNA analysis. Drone videography also accompanied the obstruction modification to capture before and after imagery. The removal of the rock obstructions through blasting has been very successful and in coming years we hope to see adult Chinook salmon being able to access the upper watershed once again!

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0330.006

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 head0.033
GPT teacher head0.279
Teacher spread0.246 · 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 designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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