Simultaneous Probe of the Charm and Bottom Quark Yukawa Couplings Using <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>t</mml:mi> <mml:mover accent="true"> <mml:mi>t</mml:mi> <mml:mo stretchy="false">¯</mml:mo> </mml:mover> <mml:mi>H</mml:mi> </mml:math> Events
Bibliographic record
Abstract
A search for the standard model Higgs boson decaying to a charm quark-antiquark pair, H→cc[over ¯], produced in association with a top quark-antiquark pair (tt[over ¯]H) is presented. The search is performed with data from proton-proton collisions at sqrt[s]=13 TeV, corresponding to an integrated luminosity of 138 fb^{-1}. Advanced machine learning techniques are employed for jet flavor identification and event classification. The Higgs boson decay to a bottom quark-antiquark pair is measured simultaneously and the observed tt[over ¯]H(H→bb[over ¯]) event rate relative to the standard model expectation is 0.91_{-0.22}^{+0.26}. The observed (expected) upper limit on the product of production cross section and branching fraction σ(tt[over ¯]H)B(H→cc[over ¯]) is 0.11 (0.13) pb at 95% confidence level, corresponding to 7.8 (8.7) times the standard model prediction. When combined with the previous search for H→cc[over ¯] via associated production with a W or Z boson, the observed (expected) 95% confidence interval on the Higgs-charm Yukawa coupling modifier, κ_{c}, is |κ_{c}|<3.5 (2.7), the most stringent constraint 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".