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Record W2061518746 · doi:10.1080/10256016.2011.631704

Identifying sources and processes controlling the sulphur cycle in the Canyon Creek watershed, Alberta, Canada

2011· article· en· W2061518746 on OpenAlexaffabout
Michael Nightingale, Bernhard Mayer

Bibliographic record

VenueIsotopes in Environmental and Health Studies · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCanyonWatershedEnvironmental scienceSulfur cycleSulfurHydrology (agriculture)GeologyChemistryGeomorphology

Abstract

fetched live from OpenAlex

Sources and processes affecting the sulphur cycle in the Canyon Creek watershed in Alberta (Canada) were investigated. The catchment is important for water supply and recreational activities and is also a source of oil and natural gas. Water was collected from 10 locations along an 8 km stretch of Canyon Creek including three so-called sulphur pools, followed by the chemical and isotopic analyses on water and its major dissolved species. The δ(2)H and δ(18)O values of the water plotted near the regional meteoric water line, indicating a meteoric origin of the water and no contribution from deeper formation waters. Calcium, magnesium and bicarbonate were the dominant ions in the upstream portion of the watershed, whereas sulphate was the dominant anion in the water from the three sulphur pools. The isotopic composition of sulphate (δ(34)S and δ(18)O) revealed three major sulphate sources with distinct isotopic compositions throughout the catchment: (1) a combination of sulphate from soils and sulphide oxidation in the bedrock in the upper reaches of Canyon Creek; (2) sulphide oxidation in pyrite-rich shales in the lower reaches of Canyon Creek and (3) dissolution of Devonian anhydrite constituting the major sulphate source for the three sulphur pools in the central portion of the watershed. The presence of H(2)S in the sulphur pools with δ(34)S values ∼30 ‰ lower than those of sulphate further indicated the occurrence of bacterial (dissimilatory) sulphate reduction. This case study reveals that δ(34)S values of surface water systems can vary by more than 20 ‰ over short geographic distances and that isotope analyses are an effective tool to identify sources and processes that govern the sulphur cycle in watersheds.

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 score0.134
Threshold uncertainty score0.336

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 head0.033
GPT teacher head0.247
Teacher spread0.214 · 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

Citations15
Published2011
Admission routes2
Has abstractyes

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