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Record W2050819086 · doi:10.2136/sssaj2004.0095

Quantification of Pollutant Lead in Forest Soils

2005· article· en· W2050819086 on OpenAlexaff
E. Steinnes, Torill Eidhammer Sjøbakk, Carmen Donisa, Maja-Lena Brännvall

Bibliographic record

VenueSoil Science Society of America Journal · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPollutionEnvironmental chemistrySoil waterDeposition (geology)PollutantEnvironmental scienceSoil horizonNitric acidChemistrySoil scienceGeologySedimentEcology

Abstract

fetched live from OpenAlex

Fifteen podzolic forest soils in Norway covering sites with a wide range of atmospheric deposition rates were assayed for their contents of pollutant Pb. Samples from the Of, Oh, E, B, and C horizons were studied. Nitric acid soluble contents of Pb and the corresponding stable Pb isotope ratios were determined by sector field inductively coupled plasma–mass spectrometry (ICP–MS). On the basis of existing knowledge on 206 Pb/ 207 Pb ratios in atmospheric deposition over Norway across time, the percentage of the Pb supplied by air pollution was calculated for the various samples and soil horizons, assuming that the C horizon was undisturbed. More than 90% of O horizon Pb was from pollution, even at remote sites in the far north. Significant fractions of Pb were pollution‐derived also in the E and B horizons at most sites. In the south, more than half of the Pb derived from air pollution has now moved to the upper mineral horizons. Stable Pb isotope ratios are a very precise tool for revealing Pb pollution in terrestrial ecosystems. The present work suggests that similar studies should be done in other parts of the world to objectively assess the anthropogenic contribution to surface soil Pb.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.252
Teacher spread0.231 · 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 teacher head, 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

Citations52
Published2005
Admission routes1
Has abstractyes

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