Diffractive<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>ρ</mml:mi></mml:mrow></mml:math>and<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>ϕ</mml:mi></mml:mrow></mml:math>production at HERA using a holographic AdS/QCD light-front meson wave function
Bibliographic record
Abstract
We use an anti--de Sitter/quantum chromodynamics holographic light-front wave function for the $\ensuremath{\rho}$ and $\ensuremath{\phi}$ mesons, in conjunction with the color glass condensate dipole cross section whose parameters are fitted to the most recent 2015 high precision HERA data on inclusive deep inelastic scattering, in order to predict the cross sections for diffractive $\ensuremath{\rho}$ and $\ensuremath{\phi}$ electroproduction. Our results suggest that the holographic meson light-front wave function is able to give a simultaneous description of $\ensuremath{\rho}$ and $\ensuremath{\phi}$ production data provided we use a set of light quark masses with ${m}_{u,d}<{m}_{s}\ensuremath{\approx}0.14\text{ }\text{ }\mathrm{GeV}$.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".