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Record W4312303797 · doi:10.46427/gold2022.8848

Chemical and isotopic constraints on carbon and sulfur dynamics in Lake Erie nearshore waters

2022· article· en· W4312303797 on OpenAlexaff
Fasong Yuan, Laodong Guo

Bibliographic record

VenueGoldschmidt2022 abstracts · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEnvironmental scienceSulfurOceanographyCarbon fibersGeologyChemistryComputer science

Abstract

fetched live from OpenAlex

While phosphorus-induced eutrophication has been studied extensively in freshwater ecosystems, cycling of other essential elements such as sulfur and carbon has not been sufficiently explored. To improve our understanding of the carbon and sulfur dynamics across the land-lake interface, concentrations of chloride (Cl), sulfate (SO 4 ), dissolved inorganic carbon (DIC), and dissolved organic carbon (DOC), the stable isotopic compositions of water (d 18 O and d 2 H) and sulfate (d 34 S SO4 and d 18 O SO4 ), and the stable and radio isotopic compositions of DIC (d 13 C DIC and D 14 C DIC ) were measured in water samples from nearshore and offshore sites at Lake Erie, the Detroit River, and other tributaries. The Detroit River and offshore waters were characterized by lower concentrations of Cl and SO 4 but higher values of d 13 C DIC and d 34 S SO4 , whereas other tributaries were featured with higher values of Cl, SO 4 , and d-excess but lower values of d 13 C DIC , D 14 C DIC , d 34 S SO4 , and d 18 O SO4 . The nearshore waters of Lake Erie had elevated values of Cl, SO 4 , and d-excess, and lower values of d 34 S SO4 and d 18 O SO4 than samples from offshore sites, consistently attesting to a strong tributary influence. The average d 34 S SO4 value decreased from the Detroit River to open Lake Erie by as high as 1.5, while there was a concomitant increase in d 18 O SO4 by 2.1. These results revealed that the carbon and sulfur dynamics in Lake Erie nearshore waters were not only affected by tributary inputs but also modulated by a range of in-lake biogeochemical processes such as CO 2 degassing, carbonate precipitation, DOC degradation, microbial sulfate reduction, and subsequent reoxidation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.998

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)0.0030.000

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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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
Published2022
Admission routes1
Has abstractyes

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