Search for pair production of first-generation leptoquarks in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"><mml:mi>p</mml:mi><mml:mover accent="true"><mml:mi>p</mml:mi><mml:mo>¯</mml:mo></mml:mover></mml:math> collisions at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.gif" overflow="scroll"><mml:msqrt><mml:mi>s</mml:mi></mml:msqrt><mml:mo>=</mml:mo><mml:mn>1.96</mml:mn><mml:mtext> TeV</mml:mtext></mml:math>
Bibliographic record
Abstract
A search for pair production of first-generation leptoquarks ( LQ ) is performed with data collected by the DØ experiment in p p ¯ collisions at s = 1.96 TeV at the Fermilab Tevatron Collider. In a sample of data corresponding to ∼ 1 fb − 1 the search has been performed on the final states with two electrons and two jets or one electron, two jets and missing transverse energy. We find our data consistent with standard model expectations. The results are combined with those found in a previous analysis of events with two jets and missing transverse energy to obtain scalar LQ mass limits. We set 95% C.L. lower limits on a scalar LQ mass of 299 GeV, 284 GeV and 216 GeV for β = 1 , β = 0.5 and β = 0.02 respectively, where β is the LQ branching ratio in the eq channel. This improves the results obtained with a lower luminosity sample from Run II of the Tevatron. Lower limits on vector LQ masses with different couplings from 357 GeV to 464 GeV for β = 0.5 are also set using this analysis.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".