MétaCan
Menu
Back to cohort
Record W4399828775 · doi:10.32920/26052544.v1

Quantifying Exceedances of Chloride Water Quality Guidelines in Niagara Escarpment Streams Around Hamilton, Ontario Using High- Frequency Data

2024· preprint· en· W4399828775 on OpenAlexaffabout
Wyatt Weatherson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsEscarpmentSTREAMSWater qualityEnvironmental scienceChlorideQuality (philosophy)Hydrology (agriculture)Water resource managementComputer scienceGeologyGeomorphologyChemistryPhysicsEcologyGeotechnical engineeringBiology

Abstract

fetched live from OpenAlex

<p>Though stream chloride concentrations ([Cl]) have been shown to be increasing in cold regions worldwide, the frequency and duration of exceedances of the freshwater chronic and acute guidelines for safe exposure of aquatic life to chloride are understudied. Streamwater [Cl] for nine watersheds located along the Niagara Escarpment around Hamilton, Ontario were modeled using concentration-conductivity regressions with high frequency specific conductivity data between March 2020 and June 2021. Analyses of [Cl] dynamics at these sites suggests that stream [Cl] occasionally exceeds the Canadian acute guideline and regularly exceeds the chronic guideline. This study highlights the dilution of stream [Cl] by precipitation events in the non-salting season, which may provide temporary relief to aquatic organisms from otherwise toxic [Cl]. These results will help ecotoxicologists identify ecologically relevant exposure durations, ultimately serving to better inform regional understanding of the risk presented to Niagara Escarpment ecosystems from increasing [Cl] concentrations.</p>

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.005
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 head0.168
GPT teacher head0.361
Teacher spread0.193 · 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.

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

Explore more

Same topicSmart Materials for ConstructionFrench-language works237,207