MétaCan
Menu
Back to cohort

Measurement of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:msup><mml:mrow><mml:mi>e</mml:mi></mml:mrow><mml:mrow><mml:mo linebreak="badbreak" linebreakstyle="after">+</mml:mo></mml:mrow></mml:msup><mml:msup><mml:mrow><mml:mi>e</mml:mi></mml:mrow><mml:mrow><mml:mo linebreak="badbreak" linebreakstyle="after">−</mml:mo></mml:mrow></mml:msup><mml:mo stretchy="false">→</mml:mo><mml:msup><mml:mrow><mml:mi mathvariant="normal">Σ</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msup><mml:msup><mml:mrow><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Σ</mml:mi></mml:mrow><mml:mrow><mml:mo stretchy="false">¯</mml:mo></mml:mrow></mml:mover></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msup></mml:math> cross sections at center-of-mass energies from 2.3864 to 3.0200 GeV

2022· article· lv· W4280511981 on OpenAlexaff
М. Н. Ачасов, P. Adlarson, S. Ahmed, M. Albrecht, A. Amoroso, Q. An, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, J. V. Bennett, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Biernat, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Z. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Çetin, J. F. Chang, W. L. Chang, G. Chelkov, D.Y. Chen, G. Chen, H.S. Chen, M.L. Chen, S.J. Chen, X.R. Chen, Y.B. Chen, G. Cibinetto, F. Cossio, X. F. Cui, J. P. Dai, X. Dai, A. Dbeyssi, R. B. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, S. X. Du, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, M. Fritsch, C. D. Fu, Y. Fu, X.L. Gao, Y. Gao, I. Garzia, E. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. Gu, M. H. Gu, S. Gu, Yuantao Gu, C. Y. Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, S. Han, T. T. Han, T. Z. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, T. Held, Y. K. Heng, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Z. Huang, N. Huesken, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. P. Ji, X. B. Ji, X. L. Ji, H. B. Jiang, X. S. Jiang, X. Y. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupść, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, L. Lavezzi, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C.H. Li, Cheng Li, D.M. Li, F. Li, G. Li, H.B. Li, H.J. Li, J.L. Li, J.Q. Li, Ke Li, L.K. Li, Lei Li, P.L. Li, P. R. Li, S.Y. Li, W.D. Li, W.G. Li, X.H. Li, X.L. Li, Z.B. Li, Z.Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, L. Z. Liao, J. Libby, C. X. Lin, B. Liu, B.J. Liu, C.X. Liu, D. Liu, D.Y. Liu, F.H. Liu, Fang Liu, Feng Liu, H.B. Liu, H.M. Liu, Huanhuan Liu, Huihui Liu, J.B. Liu, J.Y. Liu, K. Liu, K.Y. Liu, Ke Liu, L. Liu, Q. Liu, S.B. Liu, Shuai Liu, T. Liu, X. Liu, Y.B. Liu, Z.A. Liu, Z.Q. Liu, Y. F. Long, X. Lou, F. X. Lu, H. Lu, J. D. Lu, J. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L., Long Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. Ma, X.N. Ma, Xinxin Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, Κ. Peters, J. Pettersson, J. L. Ping, R. G. Ping, A. Pitka, R. Poling, V. Prasad, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, X. P. Qin, X. S. Qin, J. F. Qiu, S. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, A. Sarantsev, M. Savrié, Y. Schelhaas, C. Schnier, K. Schoenning, D. C. Shan, X. Y. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, J. J. Song, Q. Q. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. F. Sui, G. X. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, Y. J. Sun, Y. Sun, Yipeng Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, V. Thoren, B. Tsednee, I. Uman, B. Wang, B.L. Wang, C.W. Wang, D.Y. Wang, H.P. Wang, K. Wang, L.L. Wang, M. Wang, M.Z. Wang, Meng Wang, W.H. Wang, W.P. Wang, X. Wang, X.F. Wang, X.L. Wang, Y. Wang, Y. Wang, Y.D. Wang, Y.F. Wang, Y.Q. Wang, Z. Wang, Z.Y. Wang, Ziyi Wang, Zongyuan Wang, T. Weber, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J.F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, H. Xiao, S. Y. Xiao, Y. J. Xiao, Z. J. Xiao, X. H. Xie, Y. Xie, Y. H. Xie, T. Y. Xing, X. A. Xiong, G. F. Xu, J. Xu, Q. Xu, W. Xu, X. P. Xu, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, Lei Yang, R. X. Yang, S. L. Yang, Y. H. Yang, Yifan Yang, Zhi Yang, M. Ye, M.H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, W. L. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Yun Zeng, B.X. Zhang, Guangyi Zhang, H.H. Zhang, H.Y. Zhang, J.L. Zhang, J.Q. Zhang, J.W. Zhang, J.Y. Zhang, J.Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. Zhang, Lei Zhang, S. Zhang, S.F. Zhang, T.J. Zhang, X.Y. Zhang, Y. Zhang, Y.H. Zhang, Y.T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z.H. Zhang, Z.Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, Jijun Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. Zheng, B. Zhong, C. Zhong, Li Zhou, Q. Zhou, X. Zhou, X. R. Zhou, A. N. Zhu, J. Zhu, K. J. Zhu, S. H. Zhu, W. J. Zhu, X. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

Bibliographic record

VenuePhysics Letters B · 2022
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsInstitute of Particle Physics
FundersShanghai Key Laboratory for Particle Physics and CosmologyDeutsche ForschungsgemeinschaftIstituto Nazionale di Fisica NucleareUniversity of Science and Technology of ChinaVetenskapsrådetNational Natural Science Foundation of ChinaChinese Academy of SciencesRoyal SocietyKnut och Alice Wallenbergs StiftelseScience and Technology Facilities CouncilStrongInstitute of High Energy PhysicsU.S. Department of Energy
KeywordsPhysicsLuminosityColliderCenter of mass (relativistic)BaryonQuantum chromodynamicsParticle physicsElectron–positron annihilationEnergy (signal processing)Center (category theory)Function (biology)Nuclear physicsCrystallographyHadronAstrophysics

Abstract

fetched live from OpenAlex

The Born cross sections of e+e−→Σ0Σ¯0 are measured at center-of-mass energies from 2.3864 to 3.0200 GeV using data samples with an integrated luminosity of 328.5 pb−1 collected with the BESIII detector operating at the BEPCII collider. The analysis makes use of a novel reconstruction method for energies near production threshold, while a single-tag method is employed at other center-of-mass energies. The measured cross sections are consistent with earlier results from BaBar, with a substantially improved precision. The cross-section lineshape can be well described by a perturbative QCD-driven energy function. In addition, the effective form factors of the Σ0 baryon are determined. The results provide precise experimental input for testing various theoretical predictions.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.084
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0040.004
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0840.067

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 head0.015
GPT teacher head0.233
Teacher spread0.219 · 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

Citations32
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuePhysics Letters BSame topicParticle physics theoretical and experimental studiesFrench-language works237,207