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Metals in the sediments of the Huron‐Erie Corridor in North America: Factors regulating metal distribution and mobilization

2007· article· en· W1605603354 on OpenAlexaff
Ewa Szalińska, G. Doug Haffner, Ken G. Drouillard

Bibliographic record

VenueLakes & Reservoirs Science Policy and Management for Sustainable Use · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSedimentMercury (programming language)Spatial distributionEnrichment factorSettlingSortingGeologyPollutantHydrology (agriculture)Environmental scienceSedimentary depositional environmentContaminationStructural basinGeomorphologyEnvironmental engineeringEcologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract Sediment samples from the Huron‐Erie Corridor (Great Lakes, North America) were collected to quantify the relative importance of natural and anthropogenic sources of contamination, and to study the spatial metal distribution patterns of metals as a function of the characteristics of the Corridor sediments. A stratified random sampling design was used to measure the spatial patterns of metal inputs, settling and sorting along the length of the Corridor. Factors regulating metal mobilization were assessed by determining metal affinities with the total organic fraction (TOM), the mineral fraction (represented as Al), and the granulometric characteristic (represented as <0.063 mm fraction). The study revealed that anthropogenic factors primarily regulated metal distributions and mobilization throughout the Huron‐Erie Corridor. In the St. Clair and Detroit Rivers, the spatial pattern of metal distributions strongly reflected local industrial sources. In the Walpole Delta and Lake St. Clair, however, inorganic (clays) and organic (TOM) particles dominated the contaminant distribution. Sediment contamination issues throughout the Huron‐Erie Corridor were dominated by mercury, released from sources along the St. Clair and Detroit Rivers. The mean enrichment factor EF Al for mercury in these sediments has reached 68.3. Other metal pollutants were confined to the sediments in the lower depositional reach of the Corridor.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.079
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.015
GPT teacher head0.267
Teacher spread0.252 · 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

Citations11
Published2007
Admission routes1
Has abstractyes

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