Bibliographic record
Abstract
Although certain boats can avoid collisions by communicating with each other and stations on land, a network of satellites above the earth’s poles could give boats all over the planet that ability. The current system for collision-avoidance involves radio signals sent from boat-to-boat and boat-to-land. But the new system, based in space, would put satellites in the line of com¬munication. It would increase the capabilities of boats to detect each other and for land-stations to detect boats with faulty or suspicious voyage in¬formation. Adding satellites into the communica¬tion equation could make contemporary collision-avoidance technology available on a global scale. Bien que certains bateaux peuvent éviter les collisions en communiquant un à l'autre et avec les stations à terre, un réseau de satel¬lites pourrait donner bateaux sur toute la planète cette capacité. Le système actuel pour éviter l'abordage utilisent les signaux radio envoyés par bateau à bateau et bateau-à-terre, mais le nouveau système, basé dans l'espace, mettrait des satellites entres les communicants. Il aug¬menterait les capacités des bateaux à détecter entre eux et pour les stations terrestres pour détecter les bateaux avec l'information de voy¬age défective ou suspect. En ajoutant les satel¬lites dans à la communication, on pourrait ren¬dre la technologie d'évitement des collisions contemporain disponible à l'échelle mondiale.
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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".