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Record W1984719551 · doi:10.1039/c0em00561d

Mercury and methyl mercury ratios in caimans (Caiman crocodilus yacare) from the Pantanal area, Brazil

2010· article· en· W1984719551 on OpenAlexfundno aff
Bárbara Vieira, V. da S. Nunes, Maria Rosário Amaral, Alana Carmo de Oliveira, Rachel Ann Hauser‐Davis, Reinaldo Campos‐Vargas

Bibliographic record

VenueJournal of Environmental Monitoring · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsMercury (programming language)Environmental scienceBiologyZoologyGeographyEnvironmental chemistryFisheryChemistryComputer science

Abstract

fetched live from OpenAlex

The Pantanal region is the largest floodplain area in the world and of great biological importance due to its unique flora and fauna. This area is continuously undergoing increasing anthropogenic threats, and has also experienced mercury contamination associated with gold mining and other anthropogenic activities. Pantanal caimans are top-level predators, and, as such, show great potential to accumulate mercury (Hg) by biomagnification. In this study 79 specimens from four locations in the Pantanal were analyzed for total Hg and methyl mercury (MeHg) by cold vapor atomic absorption spectrometry. Total Hg contents ranged from 0.02 to 0.36 µg g(-1) (ww), and most specimens presented MeHg ratios above 70%. One of the sites, impacted by anthropogenic activities, presented significantly higher total Hg in comparison to three less impacted sites, supporting the hypothesis that caimans can, in fact, be considered effective bioindicators of ecosystem health.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.132

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 communication0.0000.000
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 head0.014
GPT teacher head0.258
Teacher spread0.245 · 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

Citations39
Published2010
Admission routes1
Has abstractyes

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