The Level of Implementation of the Department of Energy Program from the Perspective of Personnel of Doe: Basis for Sustainable and Accessible Energy for the Philippines
Bibliographic record
Abstract
Abstract Background and Objective: This study is aimed at determining the implementation level of the DOE Programs in terms of Downstream Oil Industry; Alternative Technologies and Fuels; Indigenous Energy Development; Energy Conservation and Efficiency; Renewable Energy; Power and Rural Electrification; and Overall Energy Plans. Material and Methods: The study is survey type and a questionnaire was distributed among the personnel assigned in the National Capital Region and the 3 divisions of Philippine archipelago namely Mindanao, Visyas, and Luzon, covering the last quarter of 2017 until the second quarter of 2018. The input box was consisted of the determination of the level of implementation of the DOE Programs in philippines. The Process box involved data collecting procedures from the personnel by descriptive evaluative survey supported by interviews as the basis of interpreting the study outcome. Then the data was encoded and the results were subjected to statistical treatment for interpretation and analysis. Finally, the output box pertained to the proposed acceptable and sustainable energy for Philippines. Results and Conclusion: The overall composite weighted mean of the assessment in all 4 groups were described as “Implemented”. Moreover, all the above-mentioned items except number 7 were considered “strength”. The perceptions of the level of implementation were identical. This is an indicator that the personnel has the common perception of the implementation of DOE programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".