Comparison of the environmental assessment of an identical office building with national methods
Bibliographic record
Abstract
Abstract The IEA EBC Annex 72 focuses on the assessment of the primary energy demand, greenhouse gas emissions and environmental impacts of buildings during production, construction, use (including repair and replacement) and end of life (dismantling), i.e. during the entire life cycle of buildings. In one of its activities, reference buildings (size, materialisation, operational energy demand, etc.) were defined on which the existing national assessment methods are applied using national (if available) databases and (national/regional) approaches. The “be2226” office building in Lustenau, Austria was selected as one of the reference buildings. TU Graz established a BIM model and quantified the amount of building elements as well as construction materials required and the operational energy demand. The building assessment was carried out using the same material and energy demand but applying the LCA approach used in the different countries represented by the participating Annex experts. The results of these assessments are compared in view of identifying major discrepancies. Preliminary findings show that the greenhouse gas emissions per kg of building material differ up to a factor of two and more. Major differences in the building assessments are observed in the transports to the construction site (imports) and the construction activities as well as in the greenhouse gas emissions of the operational energy demand (electricity). The experts document their practical difficulties and how they overcame them. The results of this activity are used to better target harmonisation efforts.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".