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Bioavailability of Engineered Nanoparticles in Soil Systems

2015· article· en· W1980355980 on OpenAlexaff
Ana de Santiago, Boris Constantin, Gaëlle Guesdon, Nicolas Kagambèga, Sébastien Raymond, Rosa Galvez‐Cloutier

Bibliographic record

VenueJournal of Hazardous Toxic and Radioactive Waste · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversité Laval
FundersU.S. Food and Drug Administration
KeywordsBioavailabilitySoil mesofaunaSoil waterSoil biologyEdaphicEnvironmental chemistryEnvironmental scienceSoil scienceChemistryBiology

Abstract

fetched live from OpenAlex

Nanotechnologies form a field of research that is still emerging with major gaps in knowledge regarding the behavior and potential toxicological risks of engineered nanoparticles (ENPs) in soils. While most of the studies are conducted in porous media (quartz and glass beads) and culture media, less frequently are the studies carried out in natural soils. However, the complex interactions occurring in soils, mediated by both soil components and soil organisms, are essential in bioavailability processes. Therefore, this paper is intended to highlight particularly the bioavailability of ENPs in soils. The potential release pathways of ENPs to soils are described and are faced with a lack of specific regulation and definitive nomenclature. This paper reviews a number of studies regarding ENP toxicological bioavailability on microorganisms and microfauna, mesofauna, and macrofauna inhabiting the soil, as well as on soil-plant systems. The paper especially discusses ENP behavior in soils that affect ENP bioavailability to the edaphic biota. Particular attention is paid to the factors regulating these processes [i.e., (1) ENP-dependent factors, (2) soil properties, and (3) soil components], focusing on organic matter.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.295

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.022
GPT teacher head0.242
Teacher spread0.220 · 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 designBench or experimental
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

Citations43
Published2015
Admission routes1
Has abstractyes

Explore more

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