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Record W1559960580

RETScreen 에너지 모델을 이용한 태양열 공기난방시스템 열성능 분석에 관한 연구

2003· article· ko· W1559960580 on OpenAlexaboutno aff
박상현, 김병선

Bibliographic record

Venue한국태양에너지학회 추계학술발표회 논문집 · 2003
Typearticle
Languageko
FieldEngineering
TopicEngineering Applied Research
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceEngineeringEnvironmental engineering
DOInot available

Abstract

fetched live from OpenAlex

SAH(Solar Air Heating) system has recently emerged as a new solar heating technology due to the advantage of low maintenance cost. RETScreen to design SAH system has been developed and verified by canadian national research agency, CEDRUCANMET Energy Diversification Research Laboratory). In this paper, RETScreen program model has been investigated to predict the average collector efficiency and the annual energy saving and it is demonstrated for the KMTC(KIER Module Test Cell) and the KSTC(KIER System Test Cell) located in Daejon. RETScreen case study indicated that the average collector efficiency is 76% and the annual energy saving are estimated as 1.67GJ/㎡yr. It is showing that RETScreen can simply estimate efficiency and EPHEnergy Performance Index) at early stage of design.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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 designSimulation or modeling
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
Published2003
Admission routes1
Has abstractyes

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Same venue한국태양에너지학회 추계학술발표회 논문집Same topicEngineering Applied ResearchFrench-language works237,207