Economic and Environmental Resolutions of Coal in Cement Industry
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
According to the latest statistics, the main reason of the increase of fog and haze in China lies in the increased air pollution emission caused by enlarged energy demand of the whole society every year. The pollution mainly comes from thermoelectric emissions, heavy chemical industry enterprises, automobile exhaust, residential heating in winter, living (cooking, hot water), urban construction and demolition, etc. One main reason is industrial pollution, and the pollution caused by coal-use accounts for more than 65% of the total industrial pollution. This paper aims at the useful skills of industrial coal to enable enterprises to use coal more economically and more environmentally friendly, so that enterprises can save costs, duly fulfill their social responsibilities to environmental cause and achieve economic and environmental benefits.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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