Shaping the solar Market in Colombia
Bibliographic record
Abstract
In the first quarter of 2016, Colombia faced a scenario that may looks impossible for some experts of the Colombian electricity market. Colombia should implement energy rationing as consequence of El Niño event.<br>The Colombian Government should see these events as an opportunity to increase the investment in more sustainable sources of energy to reduce the dependency of energy generation form Hydro-electric power plants without increase the use of non-renewable sources.<br>Therefore, this document contains a description of the current electricity Market in Colombia (MEM), as well as the analysis of the Australian Electricity Market (AEMO). At the same time, the comparison of the current Colombian context with the Australian context is important to understand the effectiveness of polices already implemented in Australia that will improve the creation of residential photo-voltaic projects in Colombia.<br>Finally, findings and recommendation are given in regards polices and institutions involved on the implementation of the solar market in Colombia.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".