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Record W2337694841

실내의 라돈 방출과 환기에 의한 저감방안

2014· article· ko· W2337694841 on OpenAlexaboutno aff
유호천, 김대환

Bibliographic record

Venue한국태양에너지학회 추계학술발표회 논문집 · 2014
Typearticle
Languageko
FieldSocial Sciences
TopicEnergy and Environmental Systems
Canadian institutionsnot available
Fundersnot available
KeywordsRadonGypsumEnvironmental scienceApartmentWaste managementVentilation (architecture)Environmental engineeringEngineeringCivil engineeringMaterials scienceMetallurgyMechanical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

Radon, one of the pollution sources of indoor air, is colorless, odorless, and tasteless noble gas, and is easily inhaled by humans, causing them lung cancer. The purpose of this study is to examine an amount of radon emission from gypsum boards among indoor building materials, and analyze indoor radon concentration through ventilation, which is another control method. Although it is known that 80-90% of radon flows into indoors through soil, it was also identified at high-rise apartment floors. This is judged to be resulted by building materials, and among them, gypsum board is being pointed out as the main cause. The standard of radon concentration is 148Bq/㎥ in America and Korea and 200Bq/㎥ in Canada, and Sweden is applying stricter standard to new houses (200Bq/㎥) than existing houses (400Bq/㎥). There are five gypsum board plants in Korea, Daejuk, Yeochoen, Daesan, Yeosu, and Ulsan, and gypsum boards that had been produced by each plant since 2014 were collected and then an amount of radon emission of one week was examined. As a result, max. 20Bq/㎥ was recorded, which is lower than the average indoor radon concentration, 48Bq/㎥. In addition, because an amount of radon emission from gypsum board produced in 2010 was confirmed to be 215Bq/㎥, it seems that phospho-gypsum board was converted to desulfurized gypsum board only lately, being applied by QC (Quality Control). Thus, it is needed to find out ways to control radon, ventilation or remodeling, for existing buildings, although gypsum boards of recently constructed buildings could be free from radon. For a basic way to control indoor radon spreading, ventilation should be done. For the experiment, gypsum board that produces a large amount of radon was put in a self-produced acrylic vessel, and ventilation was applied by blowing wind to it using a DC fan, and the change of an amount of radon contained in the vessel was observed. When the amount of radon 168Bq/㎥ was constantly applied by ventilation (once, wind speed 0.12m/s), it was reduced down to 16Bq/㎥ 4 days later, and when the amount of radon 303Bq/㎥ was constantly applied by ventilation (three times, wind speed 0.36m/s), it was reduced down to 30Bq/㎥ 4 days later. It is judged to be a satisfactory level because it is between 15Bq/㎥, outdoor average radon concentration, and 48Bq/㎥, indoor average radon concentration.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.003

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 head0.009
GPT teacher head0.231
Teacher spread0.221 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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