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Record W2170218036 · doi:10.1002/etc.5620211028

An evaluation of the success of dredging as remediation at a DDT-contaminated site in San Francisco Bay, California, USA

2002· article· en· W2170218036 on OpenAlexaff
Donald P. Weston, Walter M. Jarman, Gilbert Cabana, Corinne E. Bacon, Lisa A. Jacobson

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Sediment Control
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsDredgingBayEnvironmental remediationEnvironmental scienceContaminationEnvironmental chemistryEcologyEnvironmental protectionOceanographyBiologyGeologyChemistry

Abstract

fetched live from OpenAlex

Lauritzen Canal, a portion of San Francisco Bay near Richmond, California, USA, was heavily contaminated with dichlorodiphenyltrichloroethane (DDT) and dieldrin as a result of releases from a pesticide-formulating firm. In 1996 and 1997, 82,000 m3 of contaminated sediment was removed from the canal by dredging. This study evaluated the success of the dredging based largely on body burdens of DDT and its metabolites (sigmaDDT) in resident biota, with some data on sediment- and water-contaminant levels and sediment toxicity testing. Sediment disturbance during dredging introduced a pulse of sigmaDDT into the Lauritzen Canal ecosystem, and body burdens of fish and invertebrates increased 2- to 76-fold, depending on the species. Approximately 1 1/2 years after remediation, 11 of 14 indicators showed contamination comparable with or worse than the contamination that existed prior to dredging. Monitoring of mussels up to four years postdredging suggests some modest improvement, although the sigmaDDT body burden of canal mussels remained far above the norm for San Francisco Bay. The elevated sigmaDDT body burdens in biota that persisted for years after remediation reflect recent exposure and are not merely a result of slow metabolic elimination of the sigmaDDT pulse associated with dredging. Sediment sigmaDDT concentrations were low immediately after dredging, but within months, the canal bottom became covered with a veneer of fine sediment as contaminated as that that had been removed. The source of this material has not been conclusively established, but we suspect it came from slumping and erosion from the flanks of the canal beneath docks and around pilings where dredging was not done. In retrospect, either capping in place or more thorough dredging may have been more successful in reducing pesticide exposure of the biota, although there were difficulties associated with both alternatives.

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)0.001
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 score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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

Citations28
Published2002
Admission routes1
Has abstractyes

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