National Airspace System: Progress and Ongoing Challenges for the Air Traffic Organization
Bibliographic record
Abstract
Testimony issued by the Government Accountability Office with an abstract that begins "Congress's formation of the Air Traffic Organization (ATO) and the Joint Planning and Development Office (JPDO), both within the Federal Aviation Administration (FAA), represent the latest efforts to address the monumental challenges of modernizing the national airspace system (NAS) during the first quarter of the twenty-first century. For more than two decades, FAA has been working to modernize the air traffic control (ATC) system, but projects have repeatedly missed cost, schedule, and performance targets. Consequently, ATC modernization has been on GAO's list of high-risk federal programs since 1995. The ATO's focus is on a rolling 10- year outlook to operate and modernize the NAS. By contrast, the JPDO's vision is longer term, focused on coordinating the research efforts of diverse federal agencies to achieve a common goal of meeting potential air traffic demands in 2025. This statement discusses (1) GAO's assessment of the ATO's efforts to date in addressing some of the key challenges for the ATC modernization program and (2) challenges that lie ahead for the ATO and options that it could consider in addressing the needs of the NAS over the next decade, as well as longer-term needs defined by the JPDO."
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.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".