Large-Scale Promotion of Animal Dung-based Domestic Biogas Digesters through Public Private Partnership: A Successful Case of Nepal
Bibliographic record
Abstract
Large-scale promotion of small scale decentralized renewable energy technologies to achieve a part of millennium development goal remained a great challenge until recently. However, a properly implementation of a public private partnership applied in biogas sector in Nepal has shown that scaling up of small scale renewable energy technologies is feasible if a multi-stakeholder sector development approach and favorable policy as well as modality is adopted. Nepal’s biogas program has been instrumental in helping to achieve some of the Millennium Development Goals (MDGs) by creating economic and social development opportunities in a sustainable way. Such model could also be widely replicated in any other renewable energy technologies and other continent of the world. DOI: http://dx.doi.org/10.3126/hn.v8i0.4908Hydro Nepal: Journal of Water, Energy and Environment Issue No. 8, 2011 JanuaryPage: 29-33Uploaded date: 17 June, 2011
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".