Apoyos sanitarios externos requeridos durante la misión Enhanced Forward Presence III (Letonia)
Bibliographic record
Abstract
espanolEn julio de 2016 se dio luz verde a la operacion eFP (Enhanced Forward Presence), con el objetivo de proveer de defensa a los paises balticos miembros de la OTAN, frente a Rusia. Espana desplego un contingente en Letonia, cuya sanidad la compuso una celula de estabilizacion y un enfermero de enlace. En caso de necesitar apoyos sanitarios se acordo hacer uso del ROLE 1 canadiense o los servicios sanitarios civiles letones. El objetivo de este estudio fue analizar los apoyos sanitarios externos requeridos durante la mision Enhanced Forward Presence III. Material y Metodos: Se llevo a cabo un estudio transversal. Se utilizaron los 78 casos de la mision eFP-III en los que hubo que gestionar apoyo externo. El analisis estadistico se llevo a cabo a traves del GNU PSPP Statistical Analysis Software version 1.2.0-g0fb4db. Resultados: Los resultados se expresaron en frecuencias. Se hallo relacion significativa entre el tipo de apoyo requerido y el tipo de medios (militares o civiles) utilizados para su resolucion. El apoyo mas numeroso fue el odontologico, seguido del radiodiagnostico y de la fisioterapia. El mayor numero de apoyos correspondio a hombres, escala Militares Profesionales de Tropa y Marineria, resueltos por medios militares y en una unica consulta. Los medios militares resolvieron la mayoria de los casos para los que contaron con la especialidad concreta necesaria. EnglishIn July 2016, the eFP (Enhanced Forward Presence) operation was given a green light, with the aim of providing defense to the Baltic countries members of NATO, against Russia. Spain deployed a contingent in Latvia, whose health consisted of a stabilization cell and a liaison nurse. In case of needing health support, it was agreed to use the Canadian ROLE 1 or the latvian civil health services. The objective of this study was to analyze the external health support required during the Enhanced Forward Presence III mission. Material and Methods: A cross-sectional study was carried out. The 78 cases of the eFP-III mission were used in which external support had to be managed. Statistical analysis was carried out through the GNU PSPP Statistical Analysis Software version 1.2.0-g0fb4db. Results: The results were expressed in frequencies. A significant relationship was found between the type of support required and the type of means (military or civil) used to resolve it. The most numerous support was the dentist, followed by radiodiagnosis and physiotherapy. The largest number of support corresponded to men, Professional Military Troop and Maritime scale, resolved by military means and in a single consultation. The military media resolved most of the cases for which they had the necessary concrete specialty.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".