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Record W2950218198 · doi:10.82308/37735

Aquatic community monitoring following the exclusion of cattle from a small watercourse in eastern Ontario

2011· article· en· W2950218198 on OpenAlexaboutno aff
Michelle Lee Nunas

Bibliographic record

VenueeScholarship@McGill (McGill) · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsForestryGeographyRiparian zoneBenthic zoneEcologyHabitatBiology

Abstract

fetched live from OpenAlex

Previous studies on the impacts of cattle on the aquatic environment have mainly focused on cold water systems with high intensity grazing, and may be of limited relevance for assessing impacts of cattle grazing on low gradient, low intensity sites such as those in eastern Ontario. The present study looks at changes to the aquatic habitat following the removal of cattle from a watercourse. Biomonitoring was completed at an aquatic restoration site over a four year period encompassing pre- and post-implementation conditions. The initial results indicated modest improvements in the habitat and in the benthic macroinvertebrate and fish communities following exclusion of cattle from the watercourse. Trends over time suggested an increase in the proportion of sensitive benthic macroinvertebrates, a decrease in tolerant benthic species and an increase in fish density. Longer-term monitoring is required to observe changes to the aquatic communities following the growth of woody riparian vegetation.

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 score0.227
Threshold uncertainty score0.456

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.046
GPT teacher head0.222
Teacher spread0.176 · 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
Published2011
Admission routes1
Has abstractyes

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Same venueeScholarship@McGill (McGill)→Same topicFish Ecology and Management Studies→French-language works237,207→