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Record W1999911724 · doi:10.4319/lo.2001.46.4.0935

Use of size spectra and empirical models to evaluate trophic relationships in streams

2001· article· en· W1999911724 on OpenAlexafffundabout
Antoine Morin, Nathalie Bourassa, Antonella Cattaneo

Bibliographic record

VenueLimnology and Oceanography · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversité de MontréalUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiomass (ecology)Trophic levelAlgaeSTREAMSNutrientInvertebrateEcologyPrimary producersEnvironmental scienceChlorophyll aPeriphytonAbundance (ecology)BiologyPhosphorusPhytoplanktonBotanyChemistry

Abstract

fetched live from OpenAlex

We measured the biomass size distributions of algae, protozoa, and invertebrates in several streams of Eastern Ontario and Western Quebec and related assemblage biomass to nutrient (nitrogen and phosphorus) concentrations in the water. Size spectra and measurement of periphytic chlorophyll were then combined with existing empirical models to estimate primary production, invertebrate production, and grazer removal, to examine herbivory in these natural assemblages. In general, biomass of organisms increased with nutrients but the response of invertebrates was stronger than that of algae and protozoans. Secondary production (range 1.7%–4.2%) and algal removal by grazers (range 62%–175%) were high relative to primary production. This suggests that grazers exert top‐down control on algae in these streams and that increases in nutrient inputs to oligo‐ and mesotrophic streams may benefit consumers more than primary producers.

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)0.004
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.063
GPT teacher head0.261
Teacher spread0.198 · 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 designSimulation or modeling
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

Citations21
Published2001
Admission routes3
Has abstractyes

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