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Record W2379807451

Study on Several Measuring Methods of Mercury Emission From Coal-fired Power Plants

2012· article· en· W2379807451 on OpenAlexaboutno aff
An Guo

Bibliographic record

VenueProceedings of the CSEE · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)SorbentEnvironmental scienceEconomic shortageCoalAtomic absorption spectroscopyProcess engineeringChemistryWaste managementEngineeringComputer scienceAdsorptionPhysics
DOInot available

Abstract

fetched live from OpenAlex

Measuring mercury emission concentration from coal-fired power plant accurately is a key point to master the data of total mercury emission and develop the technique of mercury control.At present,the applied methods of measuring mercury emission from power plant mainly include: Ontario hydro method(OHM),continuous emissions monitoring system(Hg-CEMS),carbon sorbent traps(30B),and KMnO4-cold vapor atomic absorption spectrophotometry(HJ 543-2009).The four methods above were described and analyzed,their advantages and shortages were indicated.On these basis,some experimental studies were made to evaluate these methods deeply,the results show that: 30B and Hg-CEMS have perfect consistency in the measurement of total mercury emission;while the measuring results of HJ 543-2009 is lower than 30B.So,due to the rigorous design and strict quality control,the methods applied internationally have high accuracy.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.058
GPT teacher head0.319
Teacher spread0.261 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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Same venueProceedings of the CSEESame topicMercury impact and mitigation studiesFrench-language works237,207