Capstone Phase I Interim Safety Study, 2000/2001
Bibliographic record
Abstract
The FAA Alaska Region’s Capstone program is a joint initiative with industry to improve aviation safety and efficiency in Alaska, by using new tools and technology to provide infrastructure and services. The first phase of Capstone is in southwest Alaska, primarily in the Yukon-Kuskokwim Delta (Y-K Delta). This technology is most likely to help prevent mid-air collisions and controlled-flight-into- terrain (CFIT) accidents, which make up only a small part of the small-plane accidents in southwest Alaska but are the most likely to cause deaths. Aside from helping prevent accidents, the technology is designed to make it easier for pilots to fly—by making it easier to navigate, by providing more current weather information, and by making instrument landings possible when weather deteriorates. To learn the benefits and limitations of these new tools and technologies, the Capstone program contracted with the University of Alaska Anchorage’s Institute of Social and Economic Research and the Aviation Technology Division to evaluate aviation safety changes in the Capstone area. This Capstone Interim Safety Report describes those changes through the end of 2001.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.011 |
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".