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Record W2756914721

Tracing Industrial Nitrogen and Sulfur Emissions in the Athabasca Oil Sands Region using Stable Isotopes

2012· article· en· W2756914721 on OpenAlexaffabout
Bernadette C. Proemse, Bernhard Mayer

Bibliographic record

VenueeCite Digital Repository (University of Tasmania) · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsOil sandsEnvironmental scienceEnvironmental chemistryStable isotope ratioIsotope analysisSulfateIsotopes of nitrogenSulfurNitrateTerrestrial ecosystemδ15NDeposition (geology)NitrogenEcosystemChemistryδ13CEcologyGeologySedimentOceanographyGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The rapid development in the Athabasca Oil Sands Region (AOSR) in northeastern Alberta, Canada, has raised concerns about the impact of the industrial emissions on the surrounding terrestrial and aquatic ecosystems. Stable isotope techniques may help to trace the transport and fate of industrial emissions provided that they are isotopically distinct from background isotope ratios in environmental receptors. In order to trace nitrogen (N) and sulfur (S) emissions released by the oil sands industry, chemical and isotopic compositions of various N and S compounds in emissions, in atmospheric deposition, and in several environmental receptors were determined. It was found that δ<sup>18</sup>O values of nitrate and sulfate and Δ<sup>17</sup>O values of nitrate are indicators that constitute excellent new monitoring tools for tracing industrial N and S emissions in the surrounding environment. Application of quantitative and qualitative stable isotope tracers revealed that industrial N and S emissions were observable in the surrounding environment within ca. 30km distance to the major emission sources.

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 score0.104
Threshold uncertainty score0.408

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 communication0.0000.001
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 head0.023
GPT teacher head0.202
Teacher spread0.178 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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