Implementación de un sistema para la administración de agendas de negocios utilizadas en eventos conocidos como ruedas de negocios
Bibliographic record
Abstract
En el presente documento encontraremos en primer lugar, una explicación sobre lo que significan las agendas de negocios y los eventos denominados ruedas de negocios, además de un detalle de las necesidades y problemáticas que existían antes de la implementación del sistema. A continuación se hace una descripción del proceso que se realizó para la implementación de esta solución, dividido en cinco partes, desde el levantamiento de los requerimientos hasta el despliegue del sistema. Se hace una presentación de los beneficios obtenidos tanto por los usuarios del sistema, como por los clientes de las ruedas de negocios; y un resumen de nuevas funcionalidades que se van a implementar en un futuro.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".