Modelling and Forecasting Energy Efficiency Impact on the Human Health
Bibliographic record
Abstract
Nowadays, one of the main pollutant factors is the inefficient use and breakdown of energy technologies. Improving access to modern energy, which emits less pollution, both at home and in the community could benefit the health of many people. Besides, it could contribute to the long-term goals of sustainable development. Health is a universal indicator of progress towards sustainable energy. Given the issue’s relevance, this article examines the impact of energy on public health. The study’s purpose is to substantiate the prospects for achieving sustainable development and human well-being, which depends on the quality of the environment and could be provided by a carbon-free economy. The methodological basis of the work is general scientific research methods, such as empirical and theoretical methods, as well as systemic and functional methods. This study applied VOSviewer tools, Web of Science and Scopus analysis tools, and Google Trends to conduct a bibliometric analysis of the impact of energy factors on public health. Based on Scopus data, the findings confirmed the hypothesis concerning a growing trend of publications examining the impact of energy factors on human health. In the study framework, the VOSviewer 1.6.18 tools allowed the detection of six clusters of research streams: renewable resources, sustainable development, public, energy policy, energy efficiency, and solar energy. The authors noted that different countries research the impact of energy on public health. These issues are most actively studied in China, the USA, and India. A separate dynamics of the publications were studied for 10 countries leading in the publication activity on the subject. The Google Trends tool has identified public interest in the topic. The interest of business and industry is considered separately. The findings showed that in the first case, the interest is more in the health factor. In turn, businesses and industries pay more attention to developing renewable energy sources. Google Trends analysis of the popularity of the search query «renewable energy» identified Korea, Turkey, Nigeria, Bangladesh, and Germany as leaders in the number of queries. However, the keywords healthy leaders are New Zealand, USA, Canada, Poland, and Australia.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".