Bibliographic record
Abstract
This thesis is organized into two independent parts.In the first part, we study the prospects for constraining the Higgs boson's couplings to up and down quarks using kinematic distributions in Higgs production at the CERN Large Hadron Collider.With 3000 fb -1 of data in the four-lepton decay channel, we find that the Higgs p T distribution can be used to constrain these couplings with precision competitive to other proposed techniques.We find -0.73 κu 0.33 and -0.88 κd 0.32, where κq = (m q /m b )κ q and κ q is a multiplicative factor that modifies the Standard Model q quark Yukawa coupling.We consider some prospects for improving this method by using additional decay channels.In the second part of the thesis, we perform the standard thermal relic abundance calculation for a generic WIMP for three different forms of the self-annihilation cross section.We apply a numerical integration technique from the mathematical literature that does not appear to be well-known, but is particularly suited to this problem.First we consider s-wave annihilation and show that we are able to reproduce well-known results in the literature for the required cross section as a function of dark matter mass.Next we consider p-wave annihilation, σv rel = βv 2
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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 | 0.001 |
| 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 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".