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Record W2056986629 · doi:10.1021/ef060406i

Factors Impacting Gaseous Mercury Speciation in Postcombustion

2006· article· en· W2056986629 on OpenAlexaboutno aff
Jinsong Zhou, Zhongyang Luo, Changxing Hu, Kefa Cen

Bibliographic record

VenueEnergy & Fuels · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsFlue gasMercury (programming language)ChemistryEnvironmental chemistryElemental mercuryOrganic chemistry

Abstract

fetched live from OpenAlex

In the bench scale, gaseous mercury oxidization was investigated in postcombustion conditions with the experimental flue gas. The baseline experimental flue gas consisted of CO 2 and N 2 . Other flue-gas constituents varied with O 2, SO 2, HCl, and NO. The measurement of mercury speciation was carried out at the downstream of the reaction tube using the Ontario Hydro method. Results showed that the possible intermediates Cl and Cl 2 from HCl are the most important factors in mercury oxidization in the experimental flue gases. More mercury oxidization occurs with a higher reaction temperature and higher HCl concentration in most of experimental flue gases with HCl addition. O 2 and NO also enhance mercury oxidization in the experimental flue gases with or without HCl and SO 2 . However, the effect of SO 2 on mercury oxidization depends upon the presence of HCl.

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 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 score0.150
Threshold uncertainty score1.000

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)0.0010.000

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 head0.016
GPT teacher head0.241
Teacher spread0.224 · 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

Citations41
Published2006
Admission routes1
Has abstractyes

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