Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Concerns over climate change and other detrimental effects of conventional energy sources have resulted in the introduction of new federal government programs to promote renewable energy technologies (RETs). Two key initiatives of the Department of Natural Resources (NRCan) of the Government of Canada that are designed to further this objective are the RETScreen®International Renewable Energy Decision Support Centre and the Renewable Energy Deployment Initiative (RED!). While the emphasis of RED! is on developing the Canadian market for renewables and providing direct financial incentives for individual RET projects, RETScreen provides the tools and human capacity building to enable the successful implementation of RETs in Canada and internationally. Both programs have shared resources and pooled their strengths to attain their complementary objectives. As a result, they have achieved considerable success in their mandates and offer valuable lessons for Korea and other countries seeking effective models to disseminate renewable energy technologies. Korea is already well on the road of benefiting from this experience: the Korean network of certified RETScreen trainers will be expanded significantly via a training workshop in conjunction with the annual conference of the Korean Solar Energy Society (KSES) on November 26-27, 2003. Also, significant knowledge transfer in regard to RED! and RETScreen program design has already occurred between Canada and Korean organizations such as KSES and the Korean Institute for Energy Research (KIER). This paper is intended to provide Korean readers with an overview of the RETScreen and REDI initiatives and shows how the two interact to help bring about the \implementation of RETs in Canada and internationally, and to offer these experiences as examples for consideration in Korea.
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it