Life Cycle Carbon Emission Analyzing of Rural Residential Energy Efficiency Retrofit-A Case Study of Gansu province
Bibliographic record
Abstract
\nObjective To study and analyze the life-cycle carbon emissions of existing rural residential energy retrofit projects to provide theoretical and data support for local rural green development and sustainable construction. Methods Life cycle analysis (LCA) was used to analyze and compare the life cycle carbon emissions (LCE) of a rural residential envelope energy efficiency retrofitting project in central Gansu. Results It was found that rural dwellings have a very high potential for energy efficiency retrofitting, and the contribution of retrofitted homes to CO2 emissions reduction can reach more than 30% over the whole life cycle. Secondly, during the retrofitting process, neglected in previous studies, carbon emissions account for about a quarter of the LCE. It is concluded that introducing LCA into evaluating rural residential energy retrofit projects' energy-saving and emission reduction benefits is more scientific, reasonable, and necessary.\n
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".