MétaCan
Menu
Back to cohort
Record W2916327321 · doi:10.15332/2422474x.4030

Memoria larga en el número de horas de vuelo de aeronave de inteligencia militar de la Fuerza Aérea Colombiana

2018· article· es· W2916327321 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComunicaciones en Estadística · 2018
Typearticle
Languagees
FieldMathematics
TopicAdvanced Statistical Methods and Models
Canadian institutionsCytodiagnostics (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.319
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.436
Teacher spread0.398 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it