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Record W7000641142

Food web structure, mercury biomagnification and carbon pathways in an experimentally flooded wetland

2000· other· en· W7000641142 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2000
Typeother
Languageen
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsFood webPelagic zoneBiomagnificationTrophic levelFood chainBenthic zoneMercury (programming language)Microbial food web
DOInot available

Abstract

fetched live from OpenAlex

The objective of this thesis was to determine the role of food web structures and carbon sources in contributing to elevated organic mercury (OHg) in a flooded reservoir food web compared to a non flooded lake. Stable isotopes of carbon indicated the different sources of food energy that could potentially transfer OHg through the food web to top predators. Stable isotopes of nitrogen related trophic position of organisms to contaminant loading and allowed quantification of biomagnification. The components of the pelagic food webs in the Experimental Lake had higher concentrations of OHg relative to other food webs based on littoral benthic algal production of the Experimental Lake and food webs in the Control Lake. Consequently, the higher OHg concentrations in the pelagic food web were caused by higher OHg concentrations at the base of the pelagic food web. Consequently, this study found that impoundment affects mercury burdens in pelagic food webs more so than littoral/benthic food webs. (Abstract shortened by UMI.)

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)0.000
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.003
GPT teacher head0.134
Teacher spread0.131 · 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

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueLibrary and Archives Canada (Government of Canada)→Same topicMilitary Technology and Strategies→French-language works237,207→