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Record W1577324041 · doi:10.22621/cfn.v117i2.706

Density and Richness of Benthic Invertebrate Populations in the North Sydenham River of Southwestern Ontario (1996-2000) Compared with Those of the St. Clair River (1990-1995)

2003· article· en· W1577324041 on OpenAlexaffvenueabout
I. W. E. Harris, Colin Drury, R. R. Simard, T. Q. Zhang

Bibliographic record

VenueThe Canadian Field-Naturalist · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSpecies richnessBenthic zoneInvertebrateAbundance (ecology)Environmental scienceEcologySedimentHydrology (agriculture)GeographyOceanographyBiologyGeology

Abstract

fetched live from OpenAlex

Richness (the number of invertebrate families/sample site) and density (the number of invertebrates/sq m) of benthic populations in the North Sydenham River were measured and compared with similar estimates for the St. Clair River. Seventeen sample sites were examined from May to October over five consecutive years. At each sample site, particle size distribution of the sediment, sediment temperature, total phosphorous, total nitrogen, total carbon, and water flow rate were measured. Physical and chemical characteristics of the North Sydenham system over the 100 km run examined were less variable than those of the St. Clair. Statistically significant but weak multiple linear correlations were found for richness and density with several of the measured variables. Invertebrate populations in the North Sydenham River were less rich and less dense than those in the downstream reach of the St. Clair and exhibited a different distribution of abundance among the orders of organisms. As in the St. Clair River, some evidence of long term cycling of abundance in several families of invertebrates was found in the North Sydenham.

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 score0.097
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.021
GPT teacher head0.213
Teacher spread0.192 · 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

Citations1
Published2003
Admission routes3
Has abstractyes

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