UPC participa en el Pacific Economic Cooperation Council
Bibliographic record
Abstract
Del 2 al 5 de junio de 2013 se realizó la XXI Reunión General del Pacific Economic Cooperation Council (PECC), en Vancouver, Canadá. El evento congregó a más de 400 personas, entre ellas las autoridades políticas de Canadá y representantes del sector empresarial, académico y político de la región Asia Pacífico. La UPC participó con Marcelo Valverde Arévalo y Gustavo García Buleje, egresados de la carrera de Administración y Negocios Internacionales, y miembros activos del Centro de Estudios de Integración y Comercio de la UPC. Ambos formaron parte de las mesas de Inclusión con Crecimiento e Innovación en el Asia Pacífico. Es importante resaltar que es la primera vez que el Perú participa con delegados oficiales y jóvenes en las reuniones del PECC, siendo ésta una importante plataforma para poder afianzar y mejorar las relaciones internacionales del país con la región del Asia Pacífico. Los representantes de la UPC continuarán por seis meses las investigaciones con sus pares extranjeros, con el objetivo de presentar sus conclusiones finales a los líderes del PECC en diciembre del presente año, y brindar sus recomendaciones a las economías miembros de APEC.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.039 | 0.011 |
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".