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Record W7018587722

Distribución espacial de metales pesados y As en sedimentos 
\nsuperficiales de fondo del estuario del Río de la Plata

2014· article· es· W7018587722 on OpenAlexaboutno aff

Bibliographic record

VenueScientific Electronic Library Online (São Paulo Research Foundation, Latin American and Caribbean Center on Health Sciences Information, Conselho Nacional de Desenvolvimento Científico e Tecnológico) · 2014
Typearticle
Languagees
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsSedimentFresh waterWater qualityFish <Actinopterygii>
DOInot available

Abstract

fetched live from OpenAlex

Los sedimentos estuarinos actúan como sumidero dediversos tipos de contaminantes, por lo que son utilizados como indicadores del impacto antropogénico. Entre estos aportes, los metales se destacan debido a que pueden generar efectos tóxicos y/o letales para la biota. Además son bioacumulables y se biomagnifican a través de la trama trófica acuática. El estuario del Río de la Plata (RdlP) constituye un área de desove y cría de peces y otros organismos de interés comercial, por lo que resulta relevante conocer la contaminación metálica. El RdlP tiene una superficie de 38.800 km2 y un caudal promedio de 24.045 m3s-1, siendo sus principales afluente los Ríos Paraná y Uruguay. El presente estudio analizó muestras de sedimento superficial de fondo, colectado en 26 sitios (año 2010). Se cuantificó el contenido de Al, As, Cd, Cr, Cu, Fe, Ni, Pb, Sc y Zn, a través del método USEPA 3050b y la técnica analítica ICP-OES. La exactitud y la precisión del método fueron evaluadas por material de referencia certificado. La granulometría del sedimento estudiado indicó la predominancia de sedimentos finos (limos y arcillas), en sitios con mayores contenidos metálicos. Las concentraciones obtenidas se compararon con los valores guía del Criteria for the Assessment of Sediment Quality in Quebec and Application Frameworks (de Canadá), utilizados como criterio de evaluación para legislación ambiental: TEL (threshold effect level) y PEL (probable effect level); además se utilizaron los niveles REL (rare effect level), OEL (occasional effect level) y FEL (frequent effect level). La concentración de As y Cu fue mayor al nivel TEL en varios sitios analizados (7,2 y 19 mg/kg respectivamente). Para ningún elemento la concentración fue mayor que el PEL. Este criterio de evaluación constituye una herramienta válida para el monitoreo de la contaminación de los sedimentos del estuario, indicando posibles efectos negativos sobre la biota del RdlP

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 score0.054
Threshold uncertainty score0.107

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.016
GPT teacher head0.328
Teacher spread0.311 · 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
Published2014
Admission routes1
Has abstractyes

Explore more

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