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Record W2059920191 · doi:10.1080/10889860290777675

Snails as Biomonitors of Oil-Spill and Bioremediation Strategies

2002· article· en· W2059920191 on OpenAlexaffabout
Lucy E. J. Lee, J. Stassen, Allison E. McDonald, Caroline Culshaw, Albert D. Venosa, Kiho Lee

Bibliographic record

VenueBioremediation Journal · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans CanadaWilfrid Laurier University
Fundersnot available
KeywordsBioremediationEnvironmental scienceEnvironmental chemistryEcologyContaminationBiologyChemistry

Abstract

fetched live from OpenAlex

Aquatic and pulmonate snails were evaluated for their suitability as biomonitors of habitat recovery following an experimental oil spill in a freshwater marshland. The mystery snail, Viviparus georgianus, and the mimic pondsnail, Pseudosuccinea columella, were used as sediment quality biomonitors for a controlled oil-spill experiment at a wetland site along the St. Lawrence River (Ste. Croix, Quebec) to assess the impacts of crude oil, rates of natural recovery, and the efficacy of bioremediation treatments to enhance the bacterial degradation of residual oil in the sediments. Sediments from control sites and oiled sites with or without the application of fertilizers as bioremediation strategies, were evaluated both in situ and under controlled laboratory conditions at various time intervals. Snail survival, growth, and histopathological changes were monitored. While V. georgianus proved to be good biomonitors, P. columella appeared unaffected by the treatments. The differing sensitivity may depend on the gastropods' feeding habits. V. georgianus being a detritivore assimilated contaminants from the sediments, while P. columella, being an herbivore, did not directly assimilate contaminants. Nevertheless, snails show potential as important and ideal “tools” for testing environmental conditions because of their abundance, ease of collection, wide distribution, and relatively sedentary nature.

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 score0.237
Threshold uncertainty score0.991

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)0.0100.001

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 head0.014
GPT teacher head0.228
Teacher spread0.214 · 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

Citations29
Published2002
Admission routes2
Has abstractyes

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