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Record W1964741609 · doi:10.1002/hyp.5570

Long‐term (18‐year) changes in sulphate concentrations in two Ontario headwater lakes and their inflows in response to decreasing deposition and climate variations

2004· article· en· W1964741609 on OpenAlexafffundabout
M. Catherine Eimers, Peter J. Dillon, Shaun A. Watmough

Bibliographic record

VenueHydrological Processes · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSTREAMSDrainage basinDeposition (geology)Environmental scienceHydrology (agriculture)Acid neutralizing capacityStreamflowAcid depositionSulfateSurface waterWater yearStructural basinEnvironmental chemistryGeologyChemistrySoil scienceSoil waterGeography

Abstract

fetched live from OpenAlex

Abstract Sulphate concentrations in two headwater lakes and their major inflows were evaluated over an 18 year period (1980–81 to 1997–98) during which time sulphate bulk deposition declined by approximately 40%. The two lake catchments represent either end of the spectrum of acid sensitivity in the Muskoka–Haliburton region of Ontario. Between 1980 and 1998, sulphate concentrations in Harp and Plastic Lakes decreased, but the decrease was much less than expected (28% and 21% respectively) given the magnitude of change in deposition. Sulphate export in streams draining into the lakes greatly exceeded sulphate input to catchments in most years, which quantitatively explains the response of lake‐sulphate concentration. Furthermore, temporal patterns in mean annual sulphate concentrations in streams were similar, and appeared to be related to climate factors. Specifically, catchment export of sulphate was greater and stream‐sulphate concentrations were higher in years that had warm, dry summers, i.e. when streamflow in many catchments ceased for up to several weeks. Increased sulphate export from catchments resulted in higher sulphate concentrations in lakes, but the response of lake sulphate was not as immediate or dramatic as the response of stream sulphate to changes in catchment dryness. Factors that affect sulphate retention or export in catchments exert a strong influence on sulphate concentrations in lakes and streams and need to be considered when evaluating the response of surface water chemistry to changes in sulphate deposition. Copyright © 2004 John Wiley & Sons, Ltd.

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 score0.379
Threshold uncertainty score0.629

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 studies0.0000.000
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 head0.015
GPT teacher head0.245
Teacher spread0.230 · 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

Citations48
Published2004
Admission routes3
Has abstractyes

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