Energy cost and its impact on regulating the buildings ’ energy behaviour
Bibliographic record
Abstract
The necessity to improve the buildings ' energy behaviour was born out of the price shock caused by the oil crises in the 1970’s. The respond was expressed by national legislative acts regulating the demand for heating and ventilation. The results were important, though not always without side-effects, for example in the field of indoor air quality. Furthermore, economic and environmental considerations played an important role in determining the policies applied, the latter particularly in the 1990’s and as a result of the Kyoto and Montreal protocols. Finally, new problems, like the increasing demand for air-conditioning and its impact on the national electricity systems began to influence the way in which a building’s energy behaviour is considered. The enforcement of the European Directive on the Energy Performance of Buildings (2002/91/EC) seems to provide for the first time an integrated regulatory tool, enabling the simultaneous consideration of the energy, environmental and economic parameters of building’s design. Its implementation, which is still facing delays, will prove the degree of its efficiency. The paper discusses the evolution of these developments, as it was expressed in the framework of the energy regulations over the last thirty years, on the hand of specific examples
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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.019 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".