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Record W7026597270

Airpark Lagoon Breach - Restoring Habitat Connectivity for Fish

2016· article· en· W7026597270 on OpenAlexaboutno aff

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHabitatMarshSalt marshEstuaryChannel (broadcasting)Nursery habitatHydrology (agriculture)WetlandWatershedSubmersion (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

The Courtenay River channel is located in the K’ómoks Estuary on the eastern side of Vancouver Island. Much of the tidal salt marsh area in the channel was filled in and developed through the mid-1900’s, including diking of a 4 hectare area for the creation of a sewage lagoon in 1963. The loss of tidal salt marsh and changes in flow dynamics impacted the suitability of the area to support rearing and refuge for juvenile salmonids. The Comox Valley Project Watershed Society undertook a project to breach the lagoon dike with a large multi-plate aluminium culvert in order to reconnect the Courtenay River through the upper end of the lagoon to the estuary. Reconnecting river flow through the lagoon provides a flushing and nutrient circulating function that partially restores the original flow dynamics, thereby improving the lagoon habitat for fish. In particular juvenile salmonids will benefit from the improved and accessible habitat for rearing, foraging and refuge. Preliminary results indicate increases in usage patterns by wildlife, specifically fish and birds. Salt marsh habitat restoration was a component of the work undertaken and the project featured strong community engagement with stewardship groups and the local First Nation.

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 score0.180
Threshold uncertainty score0.358

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.018
GPT teacher head0.215
Teacher spread0.197 · 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
Published2016
Admission routes1
Has abstractyes

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