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Record W2044559410 · doi:10.4141/s04-014

Assessment of long-term fate of metals in soils: Inferences from analogues

2005· article· en· W2044559410 on OpenAlexvenueno aff
Steve Sheppard

Bibliographic record

VenueCanadian Journal of Soil Science · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsBiotaSoil waterLeaching (pedology)Environmental scienceEnvironmental chemistryPedogenesisLimitingEarth scienceSoil scienceChemistryGeologyEcology

Abstract

fetched live from OpenAlex

The assessment of the health and environmental impacts of metal contamination in soils is complicated, and in different ways than is the assessment of many other contaminants. One of the foremost problems is that the metals are often relatively immobile, so that it is necessary to verify predictions of mobility and impact far into the future. One approach is to seek analogue information: information from studies that may not have set out to measure attributes related to metal behaviour, but that none the less provide useful insights. One example would be the information on the mobility of natural clays and pedogenic metals such as iron and aluminum in soils. It is well accepted that clay particles will move downward in soils; what is less commonly inferred is that any contaminants associated with the clays will also move downward. For mobility of some metals, this may be a dominant process. Similarly, bioturbation has proven to markedly outpace leaching for many metals. This paper considers analogues related to cesium from bomb-fallout and Chernobyl, other natural radionuclide inputs to the soil, soil pedogenesis, pollen and non-metal industrialage inputs, ancient metal works, and soil fertility management. Related to biological transfers and toxicity, it considers analogy among elements an d among biota, and analogy to ecotoxicology of metals to freshwater biota. Where possible, limiting values for parameters of assessment models have been derived. Key words: Terrestrial, leaching, mobility, ecotoxicity, assessment

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.281
Teacher spread0.256 · 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.

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

Citations20
Published2005
Admission routes1
Has abstractyes

Explore more

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