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Record W4318912975 · doi:10.1039/d2em00332e

Nanoscale characterization of the sequestration and transformation of silver and arsenic in soil organic matter using atom probe tomography and transmission electron microscopy

2023· article· en· W4318912975 on OpenAlexafffund
Mozhgan Akbari Alavijeh, Michael Schindler, Mark Wirth, Odeta Qafoku, Libor Kovařík, Daniel E. Perea

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of Manitoba
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaEnvironmental Molecular Sciences Laboratory
KeywordsArsenicTransmission electron microscopyMaterials scienceFocused ion beamScanning electron microscopeAtom probeAmorphous solidOrganic matterArsenateMineralogyAnalytical Chemistry (journal)Chemical engineeringChemistryIonNanotechnologyCrystallographyMetallurgyEnvironmental chemistry

Abstract

fetched live from OpenAlex

a mineral-replacement reaction (rims) or a complete dissolution of the Ag NPs, the subsequent precipitation of acanthite NPs and their aggregation (dendrites) and Ostwald ripening (euhedral crystals). These results show the importance of OM and, specifically the mineral inclusions in the sequestration of Ag and As to less bioavailable forms such as acanthite and scorodite, respectively.

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)0.000
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 score0.314
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.234
Teacher spread0.227 · 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

Citations6
Published2023
Admission routes2
Has abstractyes

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