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Record W171509180 · doi:10.2166/wqrj.2005.037

Caging Small-Bodied Fish as an Alternative Method for Environmental Effects Monitoring (EEM)

2005· article· en· W171509180 on OpenAlexaffabout
Vince Palace, Cecilia C. Doebel, Chris L. Baron, R. E. Evans, Kerry Wautier, Jack F. Klaverkamp, Jeffrey Werner, S. Kollar

Bibliographic record

VenueWater Quality Research Journal · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsGovernment of CanadaQueen's UniversityFisheries and Oceans Canada
Fundersnot available
KeywordsFish <Actinopterygii>ConfoundingEnvironmental scienceEcologyEnvironmental stressToxicologyFisheryBiologyStatisticsMathematics

Abstract

fetched live from OpenAlex

Abstract The utility of using fish held in cages for investigating the potential effects of industrial and municipal effluents has been demonstrated. These types of exposures are able to control the influence of some confounding factors and also provide a measure of certainty with regard to exposure. However, Canada's current Environmental Effects Monitoring (EEM) Program for metal mines does not accept caged fish as a viable alternative for use in place of wild fish surveys. Concerns appear to be focused on the confounding influences of confinement stress on typical EEM endpoints. Confinement stress may be reduced in smaller-bodied fish relative to larger fish, increasing the relevance of their use for EEM. A standardized technique for deploying small-bodied fish in cages that may be useful for EEM programs is described.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.110
GPT teacher head0.430
Teacher spread0.320 · 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

Citations20
Published2005
Admission routes2
Has abstractyes

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