Bibliographic record
Abstract
Abstract The evidence of Dark Matter (DM) is one of the strongest observational arguments in favor of physics beyond the Standard Model. Despite expectations, a similar evidence has been lacking so far in collider searches, with the possible exception of B-physics discrepancies, a coherent set of persistent deviations in a homogeneous dataset consisting of b → c and b → s semi-leptonic transitions. We explore the question whether DM and the B discrepancies may have a common origin. We do so in the context of the so-called 4321 gauge model, a UV-complete and calculable setup that yields a U1 leptoquark, the by far most successful single mediator able to explain the B anomalies, along with other new gauge bosons, including a Z′. Adding to this setup a ‘minimal’ DM fermionic multiplet, consisting of a 4 under the 4321’s SU(4), we find the resulting model in natural agreement with the relic-density observation and with the most severe direct-detection bounds, in the sense that the parameter space selected by B physics is also the one favored by DM phenomenology. The DM candidate is a particle with a mass in the WIMP range, freeze-out dynamics includes a co-annihilator (the ‘rest’ of the 4 multiplet), and the most important gauge mediator in the DM sector is the Z′.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".