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Record W2048490802 · doi:10.1144/geochem2014-279

Mobile Metal Ion <sup>®</sup> analysis of European agricultural soils: bioavailability, weathering, geogenic patterns and anthropogenic anomalies

2014· article· en· W2048490802 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeochemistry Exploration Environment Analysis · 2014
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsSGS (Canada)
Fundersnot available
KeywordsWeatheringSoil waterBioavailabilityEnvironmental chemistryGeochemistryEnvironmental scienceEarth scienceAgricultureHeavy metalsGeologyChemistrySoil scienceArchaeologyGeography

Abstract

fetched live from OpenAlex

Two thousand one hundred and eight agricultural soils (0–20 cm depth) collected at a density of one sample per 2500 km 2 under the auspices of the Geochemical Mapping of Agricultural Soils (GEMAS) project over most of the European continent have been analysed using the Mobile Metal Ion (MMI ® ) partial extraction technique with ICP-MS finish. For a number of elements, notably Ce, Ni, and Ca, coherent geogenic patterns have been observed which relate to underlying lithology. For Fe and Al, coherent patterns are also observed but the effects of weathering are evident, and provide a mechanism to explain the acidity of soils in high rainfall areas. Individual anomalies, many related to anthropogenic activity (mining, metallurgy, agriculture) have been observed for Ag, Au, Cu, Pb, Cd and Zn. Comparison of the results with aqua regia digestion and the equivalent National Geochemistry Survey of Australia (NGSA) provides insights into weathering processes and the concept of bioavailability.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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