ARP4754A/ ED-79A - Guidelines for Development of Civil Aircraft and Systems - Enhancements, Novelties and Key Topics
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">ARP4754A/ED-79A guidelines addresse the development cycle for aircraft and systems that implement aircraft functions. The current trend in system design is an increasing level of integration between aircraft functions and the systems that implement them. While there can be considerable value gained when integrating systems with other systems, the increased complexity yields increased possibilities for errors, particularly with functions that are performed jointly across multiple systems. Following the Aviation Rulemaking Advisory Committee (ARAC) recommendations to respond to this increased integration which referenced ARP4754/ED-79 in advisory materials for compliance to 14CFR/CS 25.1309 (see AMC 25.1309, published in 2002 and AC25.1309-Arsenal draft) the use of ARP4754A/ED79A in aircraft certification has become increasingly widespread.</div><div class="htmlview paragraph">This presentation constitutes a comparison between the documents SAE [<span class="xref">1</span>] / EUROCAE [<span class="xref">2</span>] and SAE [<span class="xref">3</span>] / EUROCAE [<span class="xref">4</span>]; it highlights ARP4754A/ED79A enhancements, novelties and key topics (e.g. Development Assurance Level Assignment FDAL &amp; IDAL).</div></div>
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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 | 0.030 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.029 | 0.011 |
| Insufficient payload (model declined to judge) | 0.092 | 0.199 |
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".