MétaCan
Menu
Back to cohort
Record W7127072592 · doi:10.18357/wg24202226

GIS assessment of riparian reserve widths in critical habitat for the Salish Sucker (Catostomus sp.) in British Columbia since the Species at Risk Act was enacted

2023· article· W7127072592 on OpenAlexafffundabout
Natalie Bruner, Karen M. M. Steensma, Mike Pearson

Bibliographic record

VenueWestern Geography · 2023
Typearticle
Language
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsTrinity Western University
FundersTrinity Western University
KeywordsRiparian zoneHabitatSuckerVegetation (pathology)Critical habitatRiparian forestBank

Abstract

fetched live from OpenAlex

The Salish Sucker (Catostomus sp.) is a Species at Risk, primarily due to habitat loss. Riparian vegetation is an important part of Salish Sucker habitat, because it buffers stream temperatures, prevents erosion, and provides suitable habitat. In this research, the changes in riparian vegetation widths, within critical habitat for Salish Suckers that have occurred in the 17 years since the Species at Risk Act (SARA) was enacted, were measured. This was done using ArcGIS Pro to compare the 2007 and the 2021 riparian vegetation widths in the eleven watersheds containing Salish Sucker. A key finding is that watersheds west of Chilliwack experienced only a decrease in riparian vegetation, while watersheds in and east of Chilliwack experienced increases and decreases in riparian vegetation. There is a loss of 102,045 m² and a gain of 82,060 m². Therefore, the net effect is a loss of 19,985 m². The findings indicate where habitat restoration efforts should be focused.

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 score0.210
Threshold uncertainty score0.422

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.018
GPT teacher head0.274
Teacher spread0.256 · 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
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueWestern GeographySame topicFish Ecology and Management StudiesFrench-language works237,207