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Record W1974906656 · doi:10.1080/15275920600996388

Baseline Concentrations of Potentially Toxic Elements in Natural Surface Soils in Torrelles (Spain)

2006· article· en· W1974906656 on OpenAlexfundno aff
Pedro Tume, Jaume Bech, Lluís Longan, Luís Tume, Ferrán Reverter, Joan Bech, Bernardo Sepúlveda

Bibliographic record

VenueEnvironmental Forensics · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsAqua regiaSoil waterEnvironmental chemistryTrace elementBaseline (sea)ChemistryEnvironmental scienceMineralogyGeologySoil scienceMetal

Abstract

fetched live from OpenAlex

The objective of this article is to establish baseline concentrations of Ba, Cr, Cu, Ni, Pb, Sr, V, and Zn (aqua regia-extractable) in natural surface soils of the Torrelles Municipal District and to investigate the relationships between these elements and soil properties and between the element concentrations themselves. Upper baseline concentrations of these elements were (mg kg −1): Ba 272.6, Cr 40.8, Cu 31.0, Ni 29.9, Pb 68.1, Sr 83.0, V 49.7, and Zn 132.7; most corresponded with the values reported in the literature. Correlation analysis showed that total Fe and Al have the strongest relationships with trace elements.

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)0.001
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 score0.053
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.005
GPT teacher head0.211
Teacher spread0.205 · 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

Citations14
Published2006
Admission routes1
Has abstractyes

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