Sharing but not caring: collider phenomenology
Bibliographic record
Abstract
Abstract Based on a previous work on scenarios where the Standard Model and dark matter particles share a common asymmetry through effective operators at early time in the Universe and later on decouple from each other (not care), in this work, we study in detail the collider phenomenology of these scenarios. In particular, we use the experimental results from the Large Hadron Collider (LHC) to constrain the viable parameter space. Besides effective operators, we also constrain the parameter space of some representative ultraviolet complete models with experimental results from both the LHC and the Large Electron-Positron Collider. Specifically, we use measurements related to jets + missing transverse energy (MET), di-jets and photon + MET. In the case of ultraviolet models, depending on the assumptions on the couplings and masses of mediators, the derived constraints can become more or less stringent. We consider also the situation where one of the mediators has mass below 100 GeV, in this case we use the ultraviolet model to construct a new effective operator responsible for the sharing of the asymmetry and study its phenomenology.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".