REHOUSE public report: REHOUSE set of indicators selected for the impact assessment
Bibliographic record
Abstract
Summary - extract: The European Union has adopted a well-defined strategy for Energy retrofitting of the European Building stock. It aims to achieve sustainability and promote a low carbon economy. This approach not only aims at cost-saving in energy consumption but also yields substantial advantages such as decreasing CO2 emissions, minimizing demolition wastes, and enhancing the overall value of buildings. The implementation of energy efficiency measures is significantly influenced by building energy codes, which integrate energy-related requirements into the design or renovation process of buildings. These codes play a crucial role in driving the adoption of energy-efficient practices but differ from one European country to another. The Level(s) framework, as described in the REHOUSE public report D3.1 of the REHOUSE project, represents the first-ever European Commission framework aiming to improve the sustainability of buildings to assessing it throughout their life cycle. This framework establishes a list of Key Performance Indicators that allow for the evaluation and qualification of the four targeted macro-objectives of Level(s). One of the main objectives of REHOUSE work package (WP) 3 is to define the assessment methods for the planned renovation actions with the 8 renovation packages. Building upon the progress made in Task 3.1, this deliverable highlights the efforts undertaken in Task 3.2 that aims to establish the REHOUSE set of indicators selected for the impact assessment. After creating a preliminary list of KPIs based on the Level(s) indicators (T3.1), Task 3.2 aims are focused on a further refinement of the KPIs selection and adaptation to the local context of the four demonstrator buildings. The KPIs selected and defined in D3.2 cover a holistic and thus multidimensional assessment of the renovation packages and building’s performance, addressing the whole renovation value chain. After sorting the list of KPIs produced in the context of T3.1, a voting process was implemented involving the project partners. The analysis of the results allowed the selection of the main KPIs per category for the demonstrators as presented in the report. For the renovation packages, specific KPIs were already selected in the grant agreement of the REHOUSE project. This list was checked and validated through T3.2 activities by the project partners. In connection with the work carried out in WP4 (Demonstration of the 8 RPs) and WP1 (Social Innovations), the indicators selected and described in this report will allow defining the resources and instrumentations to be implemented for the evaluation of the KPIs. Further public reports of the REHOUSE project: Publications – REHOUSE
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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 | 0.022 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.049 | 0.045 |
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".