Bibliographic record
Abstract
The introduction of the warp drive metric by Alcubierre1 has aroused great interest over the past few years. Using an uncertainty-type principle, Ford and Pfenning2 proved that the warp drive transport of a spaceship in a regular bubble having a radius of 100 m is unrealistic. However, Van Den Broeck3 has shown that the situation largely improves when one uses a warp drive bubble with a small surface area and large spatial volume. Putting aside many physics problems related to the realization of the warp drive concept, we show in this paper4 how to modify Van Den Broeck's idea to improve his results. We find new lower bounds for the warp drive energy by working on parameters whose latitude has never been considered before. We also consider micro warp drive bubbles which can be treated as physical entities of their own and could possibly be used to transmit information faster than the speed of light. The conditions prevailing just after the Big Bang allow the spontaneous formation of such micro bubbles which could still be present in our period of time.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 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".