Observation of single top quark production and measurement of |<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>V</mml:mi><mml:mrow><mml:mi>t</mml:mi><mml:mi>b</mml:mi></mml:mrow></mml:msub><mml:mo stretchy="false">|</mml:mo></mml:math>with CDF
Bibliographic record
Abstract
We report the observation of electroweak single top quark production in $3.2\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ of $p\overline{p}$ collision data collected by the Collider Detector at Fermilab at $\sqrt{s}=1.96\text{ }\text{ }\mathrm{TeV}$. Candidate events in the $W+\mathrm{\text{jets}}$ topology with a leptonically decaying $W$ boson are classified as signal-like by four parallel analyses based on likelihood functions, matrix elements, neural networks, and boosted decision trees. These results are combined using a super discriminant analysis based on genetically evolved neural networks in order to improve the sensitivity. This combined result is further combined with that of a search for a single top quark signal in an orthogonal sample of events with missing transverse energy plus jets and no charged lepton. We observe a signal consistent with the standard model prediction but inconsistent with the background-only model by 5.0 standard deviations, with a median expected sensitivity in excess of 5.9 standard deviations. We measure a production cross section of ${2.3}_{\ensuremath{-}0.5}^{+0.6}(\mathrm{stat}+\mathrm{sys})\text{ }\text{ }\mathrm{pb}$, extract the value of the Cabibbo-Kobayashi-Maskawa matrix element $|{V}_{tb}|={0.91}_{\ensuremath{-}0.11}^{+0.11}(\mathrm{stat}+\mathrm{sys})\ifmmode\pm\else\textpm\fi{}0.07\text{ }\text{ }(\mathrm{\text{theory}})$, and set a lower limit $|{V}_{tb}|>0.71$ at the 95% C.L., assuming ${m}_{t}=175\text{ }\text{ }\mathrm{GeV}/{c}^{2}$.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".