CEDES: A Complete, Legitimate and Seamless Green Building Rating System
Bibliographic record
Abstract
This paper proposes a new more complete, rigorous and seamless Green Building Rating System (GBRS) than the currently used systems, known as CEDES (Comprehensive Environmental Design and Evaluation System). The objective is to design a new green building rating system (GBRS) that addresses the shortcomings of existing GBRSs. To this end, a literature review was conducted, and critiques of current GBRSs were compiled. Secondly, a hierarchical structure of evaluation categories and indicators was designed, based on a comprehensive life cycle analysis of all materials and processes used in the construction sector. The result is the CEDES system. CEDES was designed from a general taxonomic conceptual framework, so it serves both as a system of sustainable evaluation, and as a general framework to create new GBRS adapted to any environmental and socio-economic environment. The novelties and contributions of this work are: 1. A GBRS has been designed that can be used internationally (CEDES); 2. CEDES can be adapted to any environmental and socioeconomic setting by simply modifying the weight of the indicators; 3. CEDES is complete, i.e. there are no missing categories or indicators as in many existing GBRS, 4. None of its categories or indicators can be considered superfluous; 5. The relative weight of each indicator is justified and legitimized and is determined by the rest of the indicators and by a complete life cycle assessment (LCA) of all aspects of the construction process; 6. CEDES serves both to evaluate buildings and as a guide to building design with the maximum ecological and sustainable level.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".