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Record W4405098624 · doi:10.22215/etd/2024-16200

Differences in Freshwater Littoral Communities Associated with Shoreline Modification for Erosion Control in the Rideau River, Ontario

2024· dissertation· en· W4405098624 on OpenAlexfundaboutno aff
Michael Robert Dusevic

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLittoral zoneMacrophyteSpecies richnessShoreInvertebrateBiodiversityEnvironmental scienceElectrofishingEcologyAbundance (ecology)GeographyErosion controlFisheryErosionBiology

Abstract

fetched live from OpenAlex

Freshwater biological communities face multiple pressures, and their study can indicatewhat effects these pressures have on their environment.Erosion control measures along 25 km of the Rideau River's shoreline in Ontario, Canada were studied in 2022 and 2023 to compare the aquatic communities associated with modified and unmodified shoreline types.Biological assessments of macroinvertebrates using artificial substrates samplers were conducted and hardened shorelines were identified to have reduced macroinvertebrate family richness.Littoral fishes were sampled using boat electrofishing and macrophytes were sampled using quadrats.Fish abundance, diversity, species richness, and macrophyte species richness were generally lower at modified shorelines with the greatest disparity at hardened shorelines.Shoreline modifications for erosion control within the Rideau River are associated with changes to littoral communities that span macroinvertebrates, fishes, and macrophytes.These effects are relevant to shoreline management and may provide opportunity for improving shoreline condition to benefit freshwater biodiversity.

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 score0.028
Threshold uncertainty score0.089

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 studies0.0020.001
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 head0.023
GPT teacher head0.238
Teacher spread0.215 · 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
Published2024
Admission routes2
Has abstractyes

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