Libro del XIV Congreso Nacional de Ciencia y Tecnología - APANAC 2023
Bibliographic record
Abstract
La Asociación Panameña para el Avance de la Ciencia (APANAC) se complace en anunciar su XIX Congreso Nacional de Ciencia y Tecnología que se llevará a cabo del 26 al 29 de septiembre de 2023; y tiene como idea central “Panamá, Hub de las Ciencias”. Este lema proyecta la visión de país que aspiramos a través del desarrollo de la ciencia y nuestra capacidad instalada para la transferencia de conocimiento. Para ello vamos a promover nuevos canales a nivel internacional, nacional, regional, provincial y municipal que nos permitan determinar las demandas reales de nuestra sociedad y de la región. Damos la bienvenida a todos los participantes y los invitamos a ser actores dinámicos en los procesos de cambio que tanto requiere nuestro ecosistema, pensado en construir alianzas de cooperación y trabajo de Investigación + Desarrollo + Innovación (I+D+i), así como conocimientos tecnológicos utilizados a nivel mundial.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.209 | 0.097 |
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".