From E-911 to NG-911: Overview and Challenges in Ecuador
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
For years, emergency attendance institutions in Ecuador worked separately and not all of them had a 24/7 service, resulting in duplicated efforts, a waste of the scarce resources, and an absence of generalized technology. In 2012, Ecuador created an Integrated Security Service, called ECU 911, to address the need of an emergency service articulating all the first response institutions. The ECU 911 relies on the Enhanced 911 technology, having a countrywide presence. Since then, Ecuador has implemented 16 public-safety answering points and 11 decentralized operative rooms, covering all Ecuadorian territory and serving to a population of about 17 million people. The overview presented in this paper demonstrates how the advanced technology supports this new model of emergency attention service based on an Enhanced 911 platform. In addition, the achievements and challenges required to become a Next-Generation 911 service are discussed.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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