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Record W2181740060 · doi:10.2166/wqrj.2001.022

Sediment Management: Ecological and Ecotoxicological Effects Must Direct Actions

2001· article· en· W2181740060 on OpenAlexaff
Gail Krantzberg, Michael A. Zarull, John H. Hartig

Bibliographic record

VenueWater Quality Research Journal · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsMinistry of the Environment, Conservation and Parks
Fundersnot available
KeywordsSedimentRemedial actionEnvironmental scienceAction planEnvironmental resource managementEnvironmental planningHydrology (agriculture)EcologyEnvironmental remediationEngineeringGeologyContamination

Abstract

fetched live from OpenAlex

Abstract The need for guidance on the bioassessment and management of contaminated sediment has been articulated by Remedial Action Plan practitioners, the International Joint Commission, scientists, and managers in many jurisdictions. Encouragingly, a convergence of opinion, on what constitutes a comprehensive sediment assessment, is beginning. However, there continues to be a need for methods to interpret and integrate multiple pieces of information on sediment chemistry, biological information from field monitoring and laboratory sediment bioassessment in an ecologically meaningful way. This paper recommends an approach to comprehensive sediment bioassessment that is driven by the need to rehabilitate “beneficial uses” as described in the Great Lakes Water Quality Agreement. The paper also highlights advances in data interpretation that are facilitating he development of sediment management strategies.

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)0.004
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.135
GPT teacher head0.402
Teacher spread0.268 · 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

Citations1
Published2001
Admission routes1
Has abstractyes

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