Bibliographic record
Abstract
Abstract Modern urban planning in the world is nowadays facing severe problems due to the fast increase of the population and migration from villages to cities, which led countries to implementation of strategy of fast, modern urban planning to meet the needs of the population. Since the 1980s, in a context marked by increasing development in energy costs and by rising attention to the problem of global warming, countries have gradually mobilized to control their energy better and reduce the environmental footprint. However, even if there are some great successes, the deployment of renewable energies is still not well developed in developing countries such as Algeria that mainly uses fossil fuels. Considering the huge potential and good climatic conditions, developing countries should take on renewable energies for their future development. This paper aims to understand the impact of modern urban strategy on the application of solar urban planning. This study will clarify the critical role of solar electricity integration used in determining the urban solar potential in four studied regions located on three different continents: Africa, Europe and North America, in the cities of Ibenbadis (Constantine, Algeria), Saint-Hugues (Quebec, Canada), Saint-Malo (France) and Ambolobozobe (Madagascar). The results obtained will allow a comparison of the calculated solar energy potential of three urban sites, the benefits of reducing carbon dioxide as well as a comparison of solar energy costs on three continents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".