Measurement of the top-quark mass in the lepton+jets channel using a matrix element technique with the CDF II detector
Bibliographic record
Abstract
A measurement of the top-quark mass is presented using Tevatron data from proton-antiproton collisions at center-of-mass energy $\sqrt{s}=1.96\text{ }\text{ }\mathrm{TeV}$ collected with the CDF II detector. Events are selected from a sample of candidates for production of $t\overline{t}$ pairs that decay into the $\mathrm{\text{lepton}}+\mathrm{\text{jets}}$ channel. The top-quark mass is measured with an unbinned maximum likelihood method where the event probability density functions are calculated using signal and background matrix elements, as well as a set of parametrized jet-to-parton transfer functions. The likelihood function is maximized with respect to the top-quark mass, the signal fraction in the sample, and a correction to the jet energy scale (JES) calibration of the calorimeter jets. The simultaneous measurement of the JES correction (${\ensuremath{\Delta}}_{\mathrm{JES}}$) amounts to an additional in situ jet energy calibration based on the known mass of the hadronically decaying $W$ boson. Using the data sample of 578 $\mathrm{\text{lepton}}+\mathrm{\text{jets}}$ candidate events, corresponding to $3.2\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ of integrated luminosity, the top-quark mass is measured to be ${m}_{t}=172.4\ifmmode\pm\else\textpm\fi{}1.4(\mathrm{stat}+{\ensuremath{\Delta}}_{\mathrm{JES}})\ifmmode\pm\else\textpm\fi{}1.3(\mathrm{syst})\text{ }\text{ }\mathrm{GeV}/{c}^{2}$.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".