Diffractive dijet production in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mover accent="true"><mml:mi>p</mml:mi><mml:mo>¯</mml:mo></mml:mover><mml:mi>p</mml:mi></mml:math>collisions at<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msqrt><mml:mi>s</mml:mi></mml:msqrt><mml:mo mathvariant="bold">=</mml:mo><mml:mn>1.96</mml:mn><mml:mtext> </mml:mtext><mml:mtext> </mml:mtext><mml:mi>TeV</mml:mi></mml:math>
Bibliographic record
Abstract
We report on a study of diffractive dijet production in $\overline{p}p$ collisions at $\sqrt{s}=1.96\text{ }\text{ }\mathrm{TeV}$ using the CDF II detector at the Fermilab Tevatron $\overline{p}p$ collider. A data sample from $310\text{ }\text{ }{\mathrm{pb}}^{\ensuremath{-}1}$ of integrated luminosity collected by triggering on a high transverse energy jet, ${E}_{T}^{\mathrm{jet}}$, in coincidence with a recoil antiproton detected in a Roman pot spectrometer is used to measure the ratio of single-diffractive to inclusive-dijet event rates as a function of ${x}^{\overline{p}}$ of the interacting parton in the antiproton, the Bjorken-$x$, ${x}_{\mathrm{Bj}}^{\overline{p}}$, and a ${Q}^{2}\ensuremath{\approx}({E}_{T}^{\mathrm{jet}}{)}^{2}$ in the ranges ${10}^{\ensuremath{-}3}<{x}_{\mathrm{Bj}}^{\overline{p}}<{10}^{\ensuremath{-}1}$ and ${10}^{2}<{Q}^{2}<{10}^{4}\text{ }\text{ }{\mathrm{GeV}}^{2}$, respectively. Results are presented for the region of $\overline{p}$-momentum-loss fraction $0.03<{\ensuremath{\xi}}_{\overline{p}}<0.09$ and a four-momentum transfer squared ${t}_{\overline{p}}>\ensuremath{-}4\text{ }\text{ }{\mathrm{GeV}}^{2}$. The ${t}_{\overline{p}}$ dependence is measured as a function of ${Q}^{2}$ and ${x}_{\mathrm{Bj}}^{\overline{p}}$ and compared with that of inclusive single diffraction dissociation. We find weak ${x}_{\mathrm{Bj}}^{\overline{p}}$ and ${Q}^{2}$ dependencies in the ratio of single diffractive to inclusive event rates, and no significant ${Q}^{2}$ dependence in the diffractive ${t}_{\overline{p}}$ distributions.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".