House construction CO<sub>2</sub> footprint quantification: a BIM approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This paper aims to establish a baseline for carbon dioxide (CO 2 ) emissions quantification in the current residential construction process. Opportunities to reduce the environmental footprint of the homebuilding process are also identified. Design/methodology/approach CO 2 emissions of various house construction stages are quantified and utilised in a 3D building information model. This allows rapid emission computations for various house sizes, designs and materials. An intelligent database calculates emissions for different house styles with different construction processes. Findings Two construction stages (basement walls foundation and framing) were identified as high CO 2 emissions contributors. In addition, equipment operation on site, transportation to and from the site and heating for curing concrete were identified as the main sources of emissions during construction. Originality/value The paper addresses the limited attention given to CO 2 emissions during the actual construction process. The introduction of building information modeling for quantifying emissions in the construction process is of significant value. This research is pertinent to the international homebuilding industry and homebuyers who all have a role in mitigating CO 2 emissions.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it