Bibliographic record
Abstract
Space technology is increasingly becoming part of our everyday life, businesses, governments and private entities rely heavily on satellite communications for their respective dealings and transactions. On the other hand, not all transactions or businesses can be done solely through telecommunications, we often need to get on an airplane and go somewhere else to do our respective businesses and if we are on vacation we definitely need to travel. The problem is that airplane travel, although fast, sometimes is not fast enough. Today's people want convenience and when they want something they usually want it fast, especially in business. Now, imagine yourself being able to get from Montreal to Sydney to close a business deal and be back home the same day or ordering a part from Tokyo to San Juan and have it delivered it the same day. It may seem like science fiction or something too far ahead in the future, but it is not. Currently, there are nations and private companies working on different prototypes that soon will be flying in our skies and above. These space transportation systems are the future of commercial transportation, but as every human activity, they will need regulation, in this thesis we will analyze the legal issues and aspects behind these future vehicles.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".