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Record W2123249047 · doi:10.2166/wqrj.2010.008

Contaminant Trends in Suspended Sediments in the Detroit River-Lake St. Clair-St. Clair River Corridor, 2000 to 2004

2010· article· en· W2123249047 on OpenAlexaff
Julia Jia, Lina Thiessen, JoAnne Schachtschneider, Jasmine Waltho, Chris Marvin

Bibliographic record

VenueWater Quality Research Journal · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsDry weightHydrology (agriculture)Mercury (programming language)Environmental scienceSedimentEnvironmental chemistryGeologyChemistryGeomorphology

Abstract

fetched live from OpenAlex

Abstract Suspended sediments from the Detroit River-Lake St. Clair-St. Clair River corridor over the period of 2000 to 2004 were analyzed to examine the spatial distributions of contaminants including polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), and mercury. Contaminant spatial distributions were similar over the five-year study period, but concentrations varied considerably among sampling locations. Concentrations of PCBs ranged from 22 to 1,200 ng/g (dry weight) in 2004, and from 10 to 2,700 ng/g (dry weight) in 2000; concentrations of PAHs ranged from 640 to 52,000 ng/g (dry weight) in 2004, and from 240 to 82,000 ng/g (dry weight) in 2000; and concentrations of mercury ranged from 0.063 to 0.478 mg/kg (dry weight) in 2004, and from 0.060 to 0.514 mg/kg (dry weight) in 2002. The highest PCB and PAH concentrations were associated with suspended sediments in the lower and middle reaches of the Detroit River in the area of the Trenton Channel, and the outflow of the Rouge River. The spatial distributions of mercury were more consistent throughout the entire corridor, indicating the presence of sources in both the lower reaches of the Detroit River and the upper reaches of the St. Clair River. Both the Trenton Channel area of the Detroit River and the upper reaches of the St. Clair River are characterized by heavy historical industrial activity, including steel manufacturing and chlor-alkali production.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.641
Threshold uncertainty score0.714

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.057
GPT teacher head0.373
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), 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

Citations20
Published2010
Admission routes1
Has abstractyes

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