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Record W7133059205

Biogeochemical and geomorphological controls on mercury dynamics in a macrotidal salt marsh, Bay of Fundy, Canada

2004· dissertation· W7133059205 on OpenAlexaboutno aff
Angelika Karolina Bayer

Bibliographic record

VenueTSpace · 2004
Typedissertation
Language
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsSalt marshMercury (programming language)BiogeochemistryBiogeochemical cycleEstuaryBayMethylmercurySalinity
DOInot available

Abstract

fetched live from OpenAlex

Salt marsh biogeochemistry is generally dominated by sulfur transformations, and sulfate-reducing bacteria have been implicated as primary methylators of mercury (Hg). Some salt marshes have been shown to support high methylmercury (MeHg) production rates that may have adverse effects on biota, however little is known about the Hg dynamics of macrotidal salt marshes that dominate the important Bay of Fundy ecoregion in Canada. This study's aim is to provide a preliminary assessment of the distribution of, and controls on, sediment and pore water MeHg concentrations in a salt marsh heavily influenced by macrotidal activity in New Brunswick, Canada. Concentrations of bulk and dissolved total mercury (THg), MeHg, sulfate, sulfide, iron and chloride were determined along a geomorphic gradient and along the estuarine salinity gradient. THg and MeHg concentrations were frequently less than those found in the adjacent estuary, except in localized areas, suggesting a potentially important role for salt marshes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.279
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2004
Admission routes1
Has abstractyes

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