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Record W7064261693

Atrazine Contamination and Suspended Sediment Transport within Logsdon River, Mammoth Cave, Kentucky

2008· article· en· W7064261693 on OpenAlexfundno aff

Bibliographic record

VenueTopSCHOLAR (Western Kentucky University) · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsnot available
FundersMcMaster UniversityWestern Kentucky University
KeywordsAtrazineHydrology (agriculture)KarstSedimentPrecipitationTurbidityAquiferGroundwaterSurface runoffSpring (device)
DOInot available

Abstract

fetched live from OpenAlex

Understanding the potential for karst aquifer contamination by sediment-sorbed pesticides is important for cave conservation efforts in agricultural landscapes. Flow rate, water quality parameters and suspended sediment concentrations were measured in Logsdon River, a ~10km karst conduit within the Turnhole Spring Groundwater Basin of Mammoth Cave National Park to determine characteristics of storm-period transport of sediment-sorbed atrazine through a conduit-flow karst aquifer. Analysis of two independent precipitation events occurring in the Spring of 2008 from May 2-4 and May 27-29 demonstrated the rapid response of the Logsdon River to precipitation events with detections of atrazine increasing during the initial turbidity peak and decline in spC, indicating that the atrazine arrives with the initial flush of surface waters that enters the conduit. Distinct peaks of atrazine did not coincide with fine grained (silt and clay-sized) sediment peaks and concentrations of atrazine remained elevated on the falling limb of the hydrograph as turbidity declined. In addition, no systematic relation between filtered and unfiltered samples was evident. There was also exceedingly weak correlation between the concentration of atrazine and suspended sediment, suggesting that if atrazine is sorbed to fine sediment particles this sorption involves only the fractions finer than 0.22 μm.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score1.000

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 head0.010
GPT teacher head0.193
Teacher spread0.183 · 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
Published2008
Admission routes1
Has abstractyes

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