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Record W1975008351 · doi:10.1063/1.4803424

The impact of chemical aging on ice nucleating abilities of iron oxide nanoparticles in the atmosphere

2013· article· en· W1975008351 on OpenAlexaff
Nermin Eltouny, Parisa A. Ariya

Bibliographic record

VenueAIP conference proceedings · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsMcGill University
Fundersnot available
KeywordsAdsorptionBTEXNanoparticleTolueneAtmosphere (unit)Chemical engineeringIron oxideEnvironmental chemistryIron oxide nanoparticlesFreundlich equationBenzeneOxideChemistryMaterials scienceEthylbenzeneOrganic chemistryMeteorology

Abstract

fetched live from OpenAlex

In this work, we investigate the interaction of gaseous organics (BTEX) with Fe3O4 nanoparticles, a component of anthropogenic dust that contributes to urban air pollution. On the basis of adsorption isotherms collected for gaseous organics onto Fe3O4 nanoparticles by GCFID, fitted to a Freundlich adsorption model, our data suggests that toluene can adsorb and change the chemical composition of Fe3O4 nanoparticles.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.225
Teacher spread0.211 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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