Measurement of the<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>¯</mml:mo></mml:mover></mml:math>cross section in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>p</mml:mi><mml:mover accent="true"><mml:mi>p</mml:mi><mml:mo>¯</mml:mo></mml:mover></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>=</mml:mo><mml:mn>1.96</mml:mn><mml:mtext> </mml:mtext><mml:mtext> </mml:mtext><mml:mi>TeV</mml:mi></mml:math>using dilepton events with a lepton plus track selection
Bibliographic record
Abstract
This paper reports a measurement of the cross section for the pair production of top quarks in $p\overline{p}$ collisions at $\sqrt{s}=1.96\text{ }\text{ }\mathrm{TeV}$ at the Fermilab Tevatron. The data were collected from the CDF run II detector in a set of runs with a total integrated luminosity of $1.1\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$. The cross section is measured in the dilepton channel, the subset of $t\overline{t}$ events in which both top quarks decay through $t\ensuremath{\rightarrow}Wb\ensuremath{\rightarrow}\ensuremath{\ell}\ensuremath{\nu}b$, where $\ensuremath{\ell}=e$, $\ensuremath{\mu}$, or $\ensuremath{\tau}$. The lepton pair is reconstructed as one identified electron or muon and one isolated track. The use of an isolated track to identify the second lepton increases the $t\overline{t}$ acceptance, particularly for the case in which one $W$ decays as $W\ensuremath{\rightarrow}\ensuremath{\tau}\ensuremath{\nu}$. The purity of the sample may be further improved at the cost of a reduction in the number of signal events, by requiring an identified $b$ jet. We present the results of measurements performed with and without the request of an identified $b$ jet. The former is the first published CDF result for which a $b$-jet requirement is added to the dilepton selection. In the CDF data there are 129 pretag $\mathrm{\text{lepton}}+\mathrm{\text{track}}$ candidate events, of which 69 are tagged. With the tagging information, the sample is divided into tagged and untagged subsamples, and a combined cross section is calculated by maximizing a likelihood. The result is ${\ensuremath{\sigma}}_{t\overline{t}}=9.6\ifmmode\pm\else\textpm\fi{}1.2(\mathrm{stat}{)}_{\ensuremath{-}0.5}^{+0.6}(\mathrm{sys})\ifmmode\pm\else\textpm\fi{}0.6(\mathrm{lum})\text{ }\text{ }\mathrm{pb}$, assuming a branching ratio of $\mathrm{BR}(W\ensuremath{\rightarrow}\ensuremath{\ell}\ensuremath{\nu})=10.8%$ and a top mass of ${m}_{t}=175\text{ }\text{ }\mathrm{GeV}/{c}^{2}$.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.056 | 0.023 |
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".