Economic Evaluation of Environment-Friendly Streetlights on a University Campus: Using a Field Survey in Korea
Bibliographic record
Abstract
Nowadays, most illumination sources for streetlights use high intensity discharge (HID) lamps. Global concerns have been raised regarding the amount of atmospheric CO2 released due to the power consumption of HID lamps. Thus streetlights with LED and solar-energy were analyzed competitively, to evaluate the feasibility of streetlights based on environmentally-friendly products at K University. The results showed that the adoption of a LED based streetlight system and a solar-energy LED system could potentially reduce CO2 emissions by approximately 120 and 170 tons each year, respectively. While the initial investment cost of LED is higher than HID, the maintenance cost is approximately one quarter of the maintenance cost of HID. However solar-energy LED lights are not appropriate to replace campus lights because of the significantly higher cost. Since the invention of LED, the technology has been continually improving while the prices are quickly decreasing; therefore, the break-even point of investments in environmentally-friendly lights is expected to be reached much earlier than previously anticipated.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".