Near-zero energy buildings - deep energy renovation feasibility calculator
Bibliographic record
Abstract
Uslijed sve većeg broja zgrada gotovo nulte energije (NZEB, engl. near zero energy building), pojavila se potreba za alatima koji će omogućiti odabir ekonomski isplativih mjera kako bi određena zgrada zadovoljila NZEB kriterije. U radu je prikazana metoda i postupak optimizacije odabira mjera energetske učinkovitosti, a kao primjer je odabrano dvadeset zgrada javnog sektora Zagrebačke županije. Postupak se temelji na optimalnom odabiru mjera energetske učinkovitosti, gdje je funkcija cilja minimalizirati jednostavni period povrata (JPP) ili ukupnu investiciju, pri čemu je potrebno ostvariti NZEB krierije. Cilj je troškovno-optimalno obnoviti zgrade pomoću programa Baza mjera energetske učinkovitosti (BMEU) koji je napravljen u suradnji s Regionalnom energetskom agencijom sjeverozapadne Hrvatske (REGEA). Rezultat je pokazao kako se od 20 promatranih zgrada, samo 10% može dovesti do razine NZEB pomoću metoda koje se u praksi koriste. Za ostalih 90% je potrebno koristiti mjere učinkovitosti koje se u stvarnosti pokazuju neisplativima. Za potrebe proračuna je korišten Microsoft Office Excel, odnosno optimizacijski alat SOLVER.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".