Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".