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Bounds on an Anomalous Dijet Resonance in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>W</mml:mi><mml:mo>+</mml:mo><mml:mtext mathvariant="normal">jets</mml:mtext></mml:math>Production in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><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" display="inline"><mml:msqrt><mml:mi>s</mml:mi></mml:msqrt><mml:mo>=</mml:mo><mml:mn>1.96</mml:mn><mml:mtext> </mml:mtext><mml:mtext> </mml:mtext><mml:mi>TeV</mml:mi></mml:math>

2011· article· lv· W2117506067 on OpenAlexafffund
V. M. Abazov, B. Abbott, B. S. Acharya, M. Adams, T. Adams, G. D. Alexeev, G. Alkhazov, G. Alverson, G. A. Alves, M. Aoki, M. Arov, A. Askew, B. Åsman, O. Atramentov, C. Ávila, J. BackusMayes, F. Badaud, L. Bagby, B. Baldin, D. V. Bandurin, S. Banerjee, E. Barberis, P. Baringer, J. Barreto, J. F. Bartlett, U. Bassler, V. Bazterra, S. Beale, A. Bean, M. Begalli, M. Begel, C. Bélanger-Champagne, L. Bellantoni, S. B. Beri, G. Bernardi, R. Bernhard, I. A. Bertram, M. Besançon, R. Beuselinck, V. A. Bezzubov, P. C. Bhat, V. Bhatnagar, G. Blazey, S. Blessing, K. Bloom, A. Boehnlein, D. Boline, E. Boos, G. Borissov, T. Bose, A. Brandt, O. Brandt, R. Brock, G. Brooijmans, A. Bross, D. Brown, J. Brown, X. B. Bu, M. Buehler, V. Buescher, V. Bunichev, S. Burdin, T. H. Burnett, C. P. Buszello, B. Calpas, E. Camacho-Pérez, M. A. Carrasco-Lizarraga, H. Castilla-Valdez, S. Chakrabarti, D. Chakraborty, K. M. Chan, A. Chandra, G. Chen, S. Chevalier-Théry, D.K. Cho, S.W. Cho, S. Choi, B. C. Choudhary, S. Cihangir, D. R. Claes, J. Clutter, M. Cooke, W. E. Cooper, M. Corcoran, F. Couderc, M.-C. Cousinou, A. Croc, D. Cutts, A. Das, G. Davies, K. De, S. J. de Jong, E. De La Cruz–Burelo, F. Déliot, M. Demarteau, R. Demina, D. Denisov, S. P. Denisov, S. Desai, C. Deterre, K. DeVaughan, H. T. Diehl, M. Diesburg, P. F. Ding, A. Dominguez, T. Dorland, A. Dubey, L. Dudko, D. Duggan, A. Duperrin, S. Dutt, A. Dyshkant, M. Eads, D. Edmunds, J. Ellison, V. D. Elvira, Y. Enari, H. Evans, A. Evdokimov, В. Н. Евдокимов, G. Facini, T. Ferbel, F. Fiedler, F. Filthaut, W. C. Fisher, H. E. Fisk, M. Fortner, H. Fox, S. Fuess, A. Garcia-Bellido, V. Gavrilov, P. Gay, W. Geng, D. Gerbaudo, C. E. Gerber, Y. Gershtein, G. Ginther, G. Golovanov, A. G. Goussiou, P. D. Grannis, S. Greder, H. Greenlee, Z. D. Greenwood, E. M. Gregores, G. Grenier, Ph. Gris, J.-F. Grivaz, A. Grohsjean, S. Grünendahl, M. Grünewald, T. Guillemin, F. Guo, G. Gutiérrez, P. Gutierrez, A. Haas, S. Hagopian, J. Haley, L. Han, K. Harder, A. Harel, J. M. Hauptman, J. Hays, T. Head, T. Hebbeker, D. Hedin, H. Hegab, A. P. Heinson, U. Heintz, C. Hensel, I. Heredia-De La Cruz, K. Herner, G. Hesketh, M. D. Hildreth, R. Hirosky, T. Hoang, J. D. Hobbs, B. Hoeneisen, M. Hohlfeld, Z. Hubáček, N. Huske, V. Hynek, I. Iashvili, Y. Ilchenko, R. Illingworth, A. S. Ito, S. Jabeen, M. Jaffré, D. O. Jamin, A. Jayasinghe, R. Jesik, K. A. Johns, M. Johnson, D. Johnston, A. Jonckheere, P. Jonsson, J. Joshi, A. W. Jung, K. Kaadze, E. Kajfasz, D. Karmanov, P. A. Kasper, I. Katsanos, R. Kehoe, S. Kermiche, N. Khalatyan, A. Khanov, A. Kharchilava, Y. N. Kharzheev, M. H. Kirby, J. M. Kohli, A. V. Kozelov, J. Kraus, S. Kulikov, Arun Kumar, A. Kupčo, T. Kurča, V. A. Kuzmin, J. Kvita, S. Lammers, G. Landsberg, P. Lebrun, Heon Sang Lee, S. W. Lee, Whei‐May Grace Lee, J. Lellouch, L. Li, Q.Z. Li, S. M. Lietti, J. K. Lim, D. Lincoln, J. Linnemann, V. V. Lipaev, R. Lipton, Y. Liu, Z. Liu, A. Lobodenko, M. Lokajı́ček, R. Coelho Lopes De, H. J. Lubatti, R. Luna-García, A. L. Lyon, A. K. A. Maciel, D. Mackin, R. Madar, R. Magaña-Villalba, S. Malik, V. L. Malyshev, Y. Maravin, J. Martínez-Ortega, R. McCarthy, C. L. McGivern, M. M. Meijer, A. Melnitchouk, D. Menezes, P. G. Mercadante, M. Merkin, A. Meyer, J. Meyer, F. Miconi, N. K. Mondal, G. S. Muanza, M. Mulhearn, M. Naimuddin, M. Narain, R. Nayyar, H. A. Neal, J. P. Negret, P. Neustroev, S. F. Novaes, T. Nunnemann, G. Obrant, J. Orduna, N. Osman, J. Osta, G. J. Otero y Garzón, M. Padilla, A. Pal, N. Parashar, V. Parihar, S.K. Park, J. A. Parsons, R. Partridge, N. Parua, A. Patwa, B. Penning, M. Perfilov, Κ. Peters, Y. Peters, K. Petridis, G. Petrillo, P. Pétroff, R. Piegaia, M.-A. Pleier, P. L. M. Podesta-Lerma, V. M. Podstavkov, P. Polozov, А. В. Попов, M. Prewitt, D. Price, N. Prokopenko, S. Protopopescu, J. Qian, A. Quadt, B. Quinn, M. S. Rangel, K. Ranjan, P. N. Ratoff, I. Razumov, P. Renkel, M. Rijssenbeek, I. Ripp-Baudot, F. Rizatdinova, M. Rominsky, A. Ross, C. Royon, P. Rubinov, R. Ruchti, G. Safronov, G. Sajot, P. Salcido, A. Sánchez-Hernández, M. P. Sanders, B. Sanghi, A. S. Santos, G. Savage, L. Sawyer, T. Scanlon, R. D. Schamberger, Y. Scheglov, H. Schellman, T. Schliephake, S. Schlobohm, C. Schwanenberger, R. Schwienhorst, J. Sekaric, H. Severini, E. Shabalina, V. Shary, A. A. Shchukin, R. K. Shivpuri, V. Šimák, V. Sirotenko, P. Skubic, P. Slattery, D. Smirnov, K. J. Smith, G. R. Snow, J. Snow, S. Söldner‐Rembold, L. Sonnenschein, K. Soustružnı́k, J. Stark, V. Stolin, D. A. Stoyanova, M. Strauss, D. Strom, L. Stutte, L. Suter, P. Svoisky, M. Takahashi, A. J. Tanasijczuk, W. Taylor, M. Titov, V. V. Tokmenin, Y.-T. Tsai, D. Tsybychev, B. Tuchming, C. Tully, S. Uvarov, S. Uzunyan, R. Van Kooten, W. M. van Leeuwen, N. Varelas, E. W. Varnes, I. A. Vasilyev, P. Verdier, L. S. Vertogradov, M. Verzocchi, M. Vesterinen, D. Vilanova, P. Vokac, H. D. Wahl, M. Wang, J. Warchol, G. Watts, M. Wayne, M. Weber, L. 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Bibliographic record

VenuePhysical Review Letters · 2011
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsYork UniversitySimon Fraser University
FundersScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaFundação para o Desenvolvimento da UNESPCentre National de la Recherche ScientifiqueInstitut National de Physique Nucléaire et de Physique des ParticulesVetenskapsrådetConselho Nacional de Desenvolvimento Científico e TecnológicoBundesministerium für Bildung und ForschungRussian Foundation for Basic ResearchFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroKorea Science and Engineering FoundationDepartment of Science and Technology, Ministry of Science and Technology, IndiaGrantová Agentura České RepublikyFederal Agency for Science and InnovationDeutsche ForschungsgemeinschaftSecretaría de Ciencia y Técnica, Universidad de Buenos AiresNational Science FoundationScience Foundation IrelandDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)FermilabConsejo Nacional de Investigaciones Científicas y TécnicasFundação de Amparo à Pesquisa do Estado de São PauloU.S. Department of Energy
KeywordsPhysicsParticle physicsResonance (particle physics)LuminosityInvariant massProduction (economics)Nuclear physicsSpectral lineAstrophysicsQuantum mechanics

Abstract

fetched live from OpenAlex

We present a study of the dijet invariant mass spectrum in events with two jets produced in association with a $W$ boson in data corresponding to an integrated luminosity of $4.3\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ collected with the D0 detector at $\sqrt{s}=1.96\text{ }\text{ }\mathrm{TeV}$. We find no evidence for anomalous resonant dijet production and derive upper limits on the production cross section of an anomalous dijet resonance recently reported by the CDF Collaboration, investigating the range of dijet invariant mass from 110 to $170\text{ }\text{ }\mathrm{GeV}/{c}^{2}$. The probability of the D0 data being consistent with the presence of a dijet resonance with 4 pb production cross section at $145\text{ }\text{ }\mathrm{GeV}/{c}^{2}$ is $8\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}6}$.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.054
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0030.002
Scholarly communication0.0060.006
Open science0.0030.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0540.011

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.

Opus teacher head0.020
GPT teacher head0.257
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations63
Published2011
Admission routes2
Has abstractyes

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