Evaluation of Carbon Emission Factors in the Cement Industry: An Emerging Economy Context
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
The cement industry is a major contributor to carbon emissions, responsible for 5–8% of global emissions. This industry is expanding, particularly in emerging economies, and it is expected that CO2 emissions will rise by 4% by 2050. To address this critical concern, this paper identifies ten factors that contribute to carbon emissions in the cement production process through an extensive literature review and prioritises these factors using the Bayesian best–worst method. The data was gathered by conducting a methodical online survey with seven cement industry professionals in Bangladesh, with the aim of gaining insights into the emerging economy. The results illustrate that fuel burning and electricity consumption are the two greatest contributors to CO2 emissions in the cement production process. This research provides guidelines for cement industries in emerging economies on how to reduce CO2 emissions as well as suggesting areas of future research for sustainable cement production.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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