Measurement of the differential cross-section of highly boosted top quarks as a function of their transverse momentum in $\sqrt{s}$ = 8 TeV proton-proton collisions using the ATLAS detector
Bibliographic record
Abstract
CERN-LHC. Measurement of the differential cross-section for pair production of top quarks with high transverse momentum ($p_T$), with respect to the transverse momentum of the top quark, obtained using the lepton+jets channel. The hadronically decaying top quark is reconstructed as an anti-kt jet with radius parameter R=1.0 and identified with jet substructure techniques. The measurement is obtained using 20.3 fb-1 of proton--proton collisions at a center-of-mass energy of 8 TeV and is corrected at both particle-level, in a fiducial region close to the event selection, and at parton-level, for events with top quarks with $p_T$ > 300 GeV. The fiducial region is defined as (see also Table 1 of the paper): - Exactly one lepton (e or mu) - p_T(lepton) > 25 GeV and |eta(lepton)| < 2.5 - p_T(anti-kt R=0.4 jets) > 25 GeV and |eta(anti-kt R=0.4 jets)| < 2.5 - MET > 20 GeV and MET+MTW > 60 GeV (MTW is the transverse mass between the lepton and the MET) - at least one anti-kt R=0.4 jets within Delta-R < 1.5 from the lepton - at least one anti-kt R=1.0 jets with p_T > 300 GeV, mass > 100 GeV, sqrt(d_12) > 40 GeV (sqrt(d_12) is the first splitting scale) - $\Delta R$(anti-kt R=1.0 jet, anti-kt R=0.4 jet) > 1.5 and $\Delta \phi$(anti-kt R=1.0 jet, lepton) > 2.3 - At least one of the anti-kt R=0.4 jets is b-tagged among: (a) the leading jet within $\Delta R$ < 1.5 from the lepton; (b) one jet within $\Delta R$ < 1.0 from anti-kt R=1.0 jet axis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".