Search for High-Mass \boldmath$e^+e^-$ Resonances in \boldmath$p\bar{p}$ Collisions at \boldmath$\sqrt{s}=$1.96 TeV
Bibliographic record
Abstract
A search for high-mass resonances in the e{sup +}e{sup -} final state is presented based on {radical}s =1.96 TeV p{bar p} collision data from the CDF II detector at the Fermilab Tevatron from an integrated luminosity of 2.5 fb{sup -1}. The largest excess over the standard model prediction is at an e{sup +}e{sup -} invariant mass of 240 GeV/c{sup 2}. The probability of observing such an excess arising from fluctuations in the standard model anywhere in the mass range of 150-1,000 GeV/c{sup 2} is 0.6% (equivalent to 2.5 {sigma}). We set Bayesian upper limits on {sigma}(p{bar p} {yields} X) {center_dot} {Beta}(X {yields} e{sup +}e{sup -}) at the 95% credibility level, where X is a spin 1 or spin 2 particle, and we exclude the standard model coupling Z{prime} and the Randall-Sundrum graviton for {kappa}/{bar M}{sub Pl} = 0.1 with masses below 963 and 848 GeV/c{sup 2}, respectively.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".