Memoria larga en el número de horas de vuelo de aeronave de inteligencia militar de la Fuerza Aérea Colombiana
Bibliographic record
Abstract
Actualmente, el Departamento de Planeación y Estadística de la Fuerza AéreaColombiana (FAC) planifica el número mensual de horas de vuelo que tendrá cadauna de sus aeronaves mediante el promedio de las horas que estuvieron estosequipos en el aire en el trimestre inmediatamente anterior. Debido a la inexactitudde los pronósticos actuales se presentan una serie de complicaciones a la horade ejecutar el presupuesto requerido pues generalmente resulta insuficiente. En elpresente trabajo se identifica un modelo ARFIMA(p,d,q) que permite pronosticaradecuadamente las horas de vuelo de la aeronave B-350 de la Fuerza Aérea Colombiana y que puede ser empleado por el alto mando militar para tomar decisiones administrativas acertadas en la planeación y uso mensual de esta aeronave.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".