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Record W2143504668 · doi:10.1139/f08-074

Have atmospheric emissions from the Athabasca Oil Sands impacted lakes in northeastern Alberta, Canada?

2008· article· en· W2143504668 on OpenAlexafffundvenueabout
Roderick R. O. Hazewinkel, Alexander P. Wolfe, Sergi Pla‐Rabès, Kris Hadley

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsQueen's UniversityUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOil sandsBiogeochemistryEnvironmental scienceAlkalinityPaleolimnologySedimentBorealEcosystemEcologyProductivityDeposition (geology)DiatomClimate changeHydrology (agriculture)OceanographyGeologyGeographyAsphaltChemistry

Abstract

fetched live from OpenAlex

The rate of bitumen extraction in northeastern Alberta, Canada, is outpacing the state of ecological understanding of the region, so that the extent of potential disturbances caused by atmospheric deposition remains largely unknown. Atmospheric SO 2 emissions from the Fort McMurray region of Alberta (∼300 t·day –1 ) constitute ∼5% of the Canadian total. Combined with an estimated NO x production of ∼300 t·day –1 , these emissions have the potential to acidify surface waters. Diatom assemblages in dated sediment cores from eight acid-sensitive lakes were analyzed to assess the effects of acidifying emissions on boreal lake ecosystems. There is no evidence that these lakes have become acidified. Instead, many of the lakes show characteristic changes towards greater productivity and occasionally greater alkalinity. The absence of evidence for acidification does not imply that emissions from the Oil Sands are environmentally benign, but rather suggests that the biogeochemistry of these lakes differs fundamentally from well-studied acidified counterparts in northern Europe and eastern North America. Complex interactions involving in-lake alkalinity production, internal nutrient loading, and climate change appear to be driving these lakes towards the new ecological states reported.

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 score0.052
Threshold uncertainty score0.931

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.184
Teacher spread0.174 · 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

Citations77
Published2008
Admission routes4
Has abstractyes

Explore more

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