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Record W2755269164

시멘트 소성시설에서의 수은 배출특성 및 최신 측정방법 적용성 평가 연구

2017· article· ko· W2755269164 on OpenAlex
Hyung-Chun Kim, 김희진, Jong-Hyeon Kim, 강대일, 박정민, 김정훈

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venue한국대기환경학회지(국문) · 2017
Typearticle
Languageko
FieldEngineering
TopicEngineering Applied Research
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)SorbentKilnOhmEnvironmental scienceWaste managementCementCement kilnRaw materialEnvironmental chemistryChemistryMaterials scienceMetallurgyEngineeringComputer scienceElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

Recently, there has been growing interest in the emission characteristics and behavior of anthropogenic mercury compounds from emission sources. It is required to establish a standard for reliable mercury measurement method. Therefore, this study has evaluated the applicability of the new measurement method; Continuous Emission Monitoring (US EPA 30A, CEM). In addition, the reliability evaluation was conducted through Ontario Hydro Method (ASTM D6784, OHM) and Sorbent trap method (US EPA Method 30B). As a monitoring result for three months via CEM from cement kiln, the maximum mercury compounds concentration was about 600 μg/S㎥. This is because of the various of raw materials and fuel, and the absence of mercury-control device. The mercury compounds concentrations of OHM, Sorbent trap and CEM were 13.64 (3.33~32.41) μg/Sm3, 13.94 (5.97~23.44) μg/S㎥ and 14.68 (6.19~26.75) μg/S㎥, respectively. The relative standard deviations (% RSD) of the three methods were 5.1~40.9%. The result of this study suggest that it is possible to apply the CEM in the cement kiln when, QA/QC such as calibration is verified.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.007

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 head0.019
GPT teacher head0.280
Teacher spread0.260 · 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