Constraints on a Minimal Hidden Photon with Kaluza-Klein \nExcitations in Large Extra Dimensions \n
Bibliographic record
Abstract
The major purpose of this work is to combine the minimal-hidden-photon model with Large Extra Dimensions (LED). This involves confining the Standard- Model photon to a 3-brane, whilst allowing the hidden photon and graviton to occupy the higher-dimensional bulk. After integrating out the extra dimensions both the hidden photon and graviton obtain a tower of massive Kaluza-Klein (KK) modes. The Standard-Model photon obtains no KK modes, in accordance with experiment. The work begins with a discussion of the minimal hidden photon with-out KK modes, including the current constraints. In most cases existing constraints are simply quoted or rederived, but for some experiments original constraints are produced. For example new constraints from atomic spectra are produced. Significant modifications are also made to the published constraint \nfrom the SN1987a energy-loss experiment. This means properly accounting for the plasma mass of the electron, and also accounting for the modification of the kinetic-mixing parameter in a plasma. Finally constraints are produced for the minimal-hidden-photon model with KK modes. \n
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".