Bibliographic record
Abstract
This paper describes an existing worldwide satellite system - Cospas-Sarsat - that provides the valuable, humanitarian service of pinpointing the locations of disaster survivors. The system demonstrates international cooperation in space and is used in many applications. This system is unique in the way that it is funded and operated, while its use remains free of charge to the end-user in distress. Cospas-Sarsat, an international satellite system for search and rescue, began operations in 1982, and has been credited with saving thousands of lives since then. Hundreds of thousands of aviators, mariners and land users worldwide are equipped with Cospas-Sarsat distress beacons, which could help save their lives in emergency situations anywhere in the world. This paper outlines system design and operation. Cospas-Sarsat satellites provide global coverage searching for user distress signals. Tracking stations on six continents receive the satellite-relayed distress signals, compute the locations of the distress events and initiate calls for help to the appropriate rescue authorities. The paper presents the evolution, current status and future plans of the system and describes some real distress cases where it helped save lives.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".