First Search for Multijet Resonances in<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><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
Bibliographic record
Abstract
We present the first model independent search for three-jet hadronic resonances within multijet events in $\sqrt{s}=1.96\text{ }\text{ }\mathrm{TeV}$ $p\overline{p}$ collisions at the Fermilab Tevatron using the CDF II detector. Pair production of supersymmetric gluinos and squarks with hadronic $R$-parity violating decays is employed as an example of a new physics benchmark for this signature. Selection criteria based on the kinematic properties of an ensemble of jet combinations within each event help to extract signal from copious QCD background. No significant excess outside the top quark mass window is observed in data with an integrated luminosity of $3.2\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$. We place 95% confidence level limits on the production cross section $\ensuremath{\sigma}(p\overline{p}\ensuremath{\rightarrow}X{X}^{\ensuremath{'}})\ifmmode\times\else\texttimes\fi{}\mathrm{BR}(\stackrel{\texttildelow{}}{g}\stackrel{\texttildelow{}}{g}\ensuremath{\rightarrow}3\text{ }\text{ }\mathrm{\text{jet}}+3\text{ }\text{ }\mathrm{\text{jet}})$ where $X$, ${X}^{\ensuremath{'}}=\stackrel{\texttildelow{}}{g}$, $\stackrel{\texttildelow{}}{q}$, or $\stackrel{\texttildelow{}}{\overline{q}}$, with $\stackrel{\texttildelow{}}{q}$, $\stackrel{\texttildelow{}}{\overline{q}}\ensuremath{\rightarrow}\stackrel{\texttildelow{}}{g}+\mathrm{\text{jet}}$, as a function of gluino mass, in the range of $77\text{ }\text{ }\mathrm{GeV}/{c}^{2}$ to $240\text{ }\text{ }\mathrm{GeV}/{c}^{2}$.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".