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Record W1678730115 · doi:10.1063/1.2747494

Mercury Emission Measurement in Coal-Fired Boilers by Continuous Mercury Monitor and Ontario Hydro Method

2007· article· en· W1678730115 on OpenAlexaboutno aff
Yanqun Zhu, Jinsong Zhou, Sheng He, Xiaoshu Cai, Changxin Hu, Jianming Zheng, Le Zhang, Zhongyang Luo, Kefa Cen

Bibliographic record

VenueAIP conference proceedings · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)Elemental mercuryEnvironmental chemistryBoiler (water heating)ChemistryEnvironmental scienceWaste managementComputer scienceFlue gasEngineering

Abstract

fetched live from OpenAlex

The mercury emission control approach attaches more importance. The accurate measurement of mercury speciation is a first step. Because OH method (accepted method) can’t provide the real‐time data and 2‐week time for results attained, it’s high time to seek on line mercury continuous emission monitors(Hg‐CEM). Firstly, the gaseous elemental and oxidized mercury were conducted to measure using OH and CEM method under normal operation conditions of PC boiler after ESP, the results between two methods show good consistency. Secondly, through ESP, gaseous oxidized mercury decrease a little and particulate mercury reduce a little bit, but the elemental mercury is just the opposite. Besides, the WFGD system achieved to gaseous oxidized mercury removal of 53.4%, gaseous overall mercury and elemental mercury are 37.1% and 22.1%, 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.154
Threshold uncertainty score0.306

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.030
GPT teacher head0.273
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2007
Admission routes1
Has abstractyes

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