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Record W3098329005

RETScreen을 활용한 건물에서의 지열 히트펌프 시스템 적용 사전 분석연구

2020· article· ko· W3098329005 on OpenAlex

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

Venue태양에너지(한국태양에너지학회 논문집) · 2020
Typearticle
Languageko
FieldSocial Sciences
TopicEnergy and Environmental Systems
Canadian institutionsnot available
Fundersnot available
KeywordsEnergy consumptionHeat pumpRenewable energyEnvironmental scienceEngineeringGreenhouse gasCivil engineeringEnvironmental engineeringMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Korea government published renewable energy obligation policy that public building must be supplied some part of total consumption energy (2019: 27%, 2020: 30%). RETScreen is freely available global energy tool that developed by Canadian National Energy Laboratory to quantify energy saving to compare conventional system. This program can be performed energy modeling, cost analysis, greenhouse gas emission analysis and financial analysis. In this study, GSHP (Ground source heat pump) heating and cooling system were studied for the energy deliverly and ROI (Return On Investment) in an office building. Three cases were studied according to the number of HP (Heat pump) units for the 1,000m2 office building located in Daejeon. Results indicated that the energy delivery of the case 1 (1 HP unit) covered 57% of the office building heating and cooling energy consumption. The case 2 (2 HP units) covered 87.8% and the case 3 (3 HP units) covered 96.8% of the office building energy consumption. The ROI of the case 1 indicated 7.9 years. While 8.2 years for the case 2 and 9.7 years for the case 3.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.715
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.009

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 head0.033
GPT teacher head0.246
Teacher spread0.213 · 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