Preoperational testing of data link-based air traffic management systems in Magadan, Far East Russia
Bibliographic record
Abstract
The Global Positioning System (GPS) has been used in many different applications. This paper discusses one such application: the surveillance of commercial aircraft in a developing airspace environment. GPS provides system users with the ability to determine their own position with an accuracy, reliability and cost that is unprecedented. Voice procedures augmented by radar have been the primary tools for air traffic surveillance since the end of World War II. But for some countries the equipage of aircraft with GPS and a data link capable of carrying position reports to the ATC authorities is providing a viable alternative to long-range secondary radar systems. In 1995, ARINC installed and demonstrated equipment in Magadan, Russia, which permits air traffic controllers of MAGADANAEROCONTROL to monitor GPS position reports generated by aircraft as far away as Canada and the South Pacific. The position reports were displayed against maps and flight tracks. This equipment has clearly demonstrated an alternative technology for the upgrading of the ATC system in Siberia and other remote areas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".