Towards a Natural Theory of Dark Energy: Supersymmetric Large Extra Dimensions
Bibliographic record
Abstract
The first part of this article summarizes the evidence for Dark Energy and Dark Matter, as well as the naturalness issues which plague current theories of Dark Energy. The main point of this part is to argue why these naturalness issues should provide the central theoretical guidance for the search for a successful theory. The second part of the article describes the present status of what I regard as being the best mechanism yet proposed for addressing this issue: Six‐dimensional Supergravity with submillimetre‐sized Extra Dimensions (Supersymmetric Large Extra Dimensions, or SLED for short). Besides summarizing the SLED proposal itself, this section also describes the tests which this model has passed, the main criticisms which have been raised, and the remaining challenges which remain to be checked. The bottom line is that the proposal survives the tests which have been completed to date, and predicts several distinctive experimental signatures for cosmology, tests of gravity and for accelerator‐based particle physics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".