MétaCan
Menu
Back to cohort
Record W3185417069 · doi:10.1002/lol2.10202

Effects of chloride and nutrients on freshwater plankton communities

2021· article· en· W3185417069 on OpenAlexaffabout
Danielle Greco, Shelley E. Arnott, Isabelle B. Fournier, Brandon S. Schamp

Bibliographic record

VenueLimnology and Oceanography Letters · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsUniversité LavalCenter for Northern StudiesAlgoma UniversityQueen's University
Fundersnot available
KeywordsPhytoplanktonPlanktonNutrientZooplanktonSpecies richnessContext (archaeology)Water qualityAbundance (ecology)Biomass (ecology)EcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Abstract Increasing chloride concentrations threaten freshwater zooplankton. We questioned the protectiveness of the Canadian Water Quality Guideline for chloride because it is based on individual species studied under laboratory conditions and does not account for potential interactive factors, such as nutrient concentration. We exposed plankton communities to 30 chloride concentration increments for 6 weeks, crossed with either ambient or high nutrient treatments. Total zooplankton abundance, biomass, and richness declined with increasing chloride, with losses observed below the Canadian Water Quality Guideline. Nutrients did not affect the impact of chloride on zooplankton. Phytoplankton and protist responses varied by nutrient level. Under low nutrients, phytoplankton and protist abundance, biomass, and richness increased with chloride. Under high nutrients, phytoplankton and protist abundance and biomass were unaffected while richness decreased with chloride. These results indicate that current water quality guidelines do not sufficiently protect plankton and that nutrient context may alter phytoplankton and protist response.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.307
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.180
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 teacher head, 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

Citations36
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueLimnology and Oceanography LettersSame topicEnvironmental Toxicology and EcotoxicologyFrench-language works237,207