Bibliographic record
Abstract
We point out that the existence of metastable, $\ensuremath{\tau}>{10}^{3}\text{ }\text{ }\mathrm{s}$, negatively charged electroweak-scale particles (${X}^{\ensuremath{-}}$) alters the predictions for lithium and other primordial elemental abundances for $A>4$ via the formation of bound states with nuclei during big bang nucleosynthesis. In particular, we show that the bound states of ${X}^{\ensuremath{-}}$ with helium, formed at temperatures of about $T={10}^{8}\text{ }\text{ }\mathrm{K}$, lead to the catalytic enhancement of $^{6}\mathrm{Li}$ production, which is 8 orders of magnitude more efficient than the standard channel. In particle physics models where subsequent decay of ${X}^{\ensuremath{-}}$ does not lead to large nonthermal big bang nucleosynthesis effects, this directly translates to the level of sensitivity to the number density of long-lived ${X}^{\ensuremath{-}}$ particles ($\ensuremath{\tau}>{10}^{5}\text{ }\text{ }\mathrm{s}$) relative to entropy of ${n}_{{X}^{\ensuremath{-}}}/s\ensuremath{\lesssim}3\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}17}$, which is one of the most stringent probes of electroweak scale remnants known to date.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".