Search for<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>W</mml:mi><mml:mi>Z</mml:mi><mml:mo mathvariant="bold">+</mml:mo><mml:mi>Z</mml:mi><mml:mi>Z</mml:mi></mml:math>production with<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mtext mathvariant="normal">missing transverse energy</mml:mtext><mml:mo mathvariant="bold">+</mml:mo><mml:mtext mathvariant="normal">jets</mml:mtext></mml:math>with<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>b</mml:mi></mml:math>enhancement 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
Diboson production ($WW+WZ+ZZ$) has been observed at the Tevatron in hadronic decay modes dominated by the $WW$ process. This paper describes the measurement of the cross section of $WZ$ and $ZZ$ events in final states with large ${\mathrm{E\ensuremath{\llap{\not\;}}}}_{T}$ and using $b$-jet identification as a tool to suppress $WW$ contributions. Because of the limited energy resolution, we cannot distinguish between partially hadronic decays of $WZ$ and $ZZ$, and we measure the sum of these processes. The number of signal events is extracted using a simultaneous fit to the invariant mass distribution of the two jets for events with two $b$-jet candidates and events with fewer than two $b$-jet candidates. We measure a cross section $\ensuremath{\sigma}(p\overline{p}\ensuremath{\rightarrow}WZ,ZZ)={5.8}_{\ensuremath{-}3.0}^{+3.6}\text{ }\text{ }\mathrm{pb}$, in agreement with the standard model.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.582 | 0.551 |
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".