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Record W2133685639 · doi:10.1080/15320380500506255

Baseline Levels of Metals in Volcanic Soils of the Azores (Portugal)

2006· article· en· W2133685639 on OpenAlexfundno aff
André F.S. Amaral, J. Virgílio Cruz, Regina Tristão da Cunha, Armindo Rodrigues

Bibliographic record

VenueSoil and Sediment Contamination An International Journal · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaCanadian Immunization Research Network
KeywordsSoil waterVolcanoSiltTrace metalEnvironmental chemistryGeologyVolcanismOrganic matterVolcanic ashEnvironmental scienceHorizonGranulometryGeochemistryEarth scienceSoil scienceMetalChemistryGeomorphologyTectonicsSediment

Abstract

fetched live from OpenAlex

Data on metal concentrations present in the soils of the Azores (Portugal) are scarce. The goal of this study was to measure the current levels of several metals in the top horizon of soils of two areas, distinguishable by their volcanic activity and physical characteristics, in order to establish some baseline concentrations of these elements. Soil samples were taken in similar ways from five sites in a volcanically active area and another five sites in an area without volcanic activity. Particle-size fractions, % organic matter, moisture content, pH, and major and trace elements compositions were measured. In general, the concentrations of trace metals in the soils from Santa Maria (inactive volcanism) were higher than those from Furnas (active volcanism), with the exception of Zn. The soils from Furnas, which have slightly lower pH and less % clay-silt than Santa Maria, will probably make such trace metals as Zn become more readily bioaccessible, and therefore pose a larger threat to living organisms inhabiting these soils.

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 score0.024
Threshold uncertainty score0.048

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.249
Teacher spread0.237 · 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

Citations36
Published2006
Admission routes1
Has abstractyes

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