The influence of implementing electronic flight bag application on aviation safety mediated by the optimization of human resources
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.
Bibliographic record
Abstract
The unintegrated use of information technology in the cockpit of Garuda aircraft was the electronic flight bag, with the application of the Garuda electronic flight manual and the Garuda electronic airway manual. This gap would cause potential negligence and delay in distributing paper documents or manuals to the aircraft of Garuda Indonesia Airline. It was necessary to study whether the use of Garuda electronic flight manual software and Garuda electronic airway manual could ease the duties of the Pilot on board the aircraft. This research aimed to know the influence of implementing the Garuda electronic flight manual and the Garuda electronic airway manual on flight safety by optimizing human resources. The study used the Path Analysis method. The samples of this research were 30 pilots as the users and processors of the Garuda electronic flight manual and the Garuda electronic airway manual. The study found that the variable of flight safety was directly influenced by the implementation of the Garuda electronic flight manual, the Garuda electronic airway manual, and the optimization of human resources. In addition, implementing the Garuda electronic flight manual and the Garuda electronic airway manual was the variable influencing flight safety at most.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it