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Record W4416624439 · doi:10.1007/jhep11(2025)111

Measurement of the Born cross section for $$ {e}^{+}{e}^{-}\to p{K}^{-}{K}^{-}{\overline{\Xi}}^{+} $$ at $$ \sqrt{s}=3.5\hbox{--} 4.9 $$ GeV

2025· article· en· W4416624439 on OpenAlexaff
M. Ablikim, М. Н. Ачасов, P. Adlarson, X. Ai, R. Aliberti, A. Amoroso, Q. An, Y. Bai, O. Bakina, Y. Ban, H. Bao, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann, Hao Cai, M. H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Çetin, X. Chai, J. F. Chang, G. R., Yuzhi Che, G. Chelkov, C. H. Chen, G. Chen, H. S. Chen, H. Y. Chen, M. L. Chen, S. J. Chen, S. L. Chen, Shaomin Chen, T. Chen, Xurong Chen, X. T. Chen, X. Y. Chen, Yuanbo Chen, Y. Q. Chen, Zhuojun Chen, Z. K. Chen, S.-K. Choi, X. Chu, G. Cibinetto, F. Cossio, J. Cottee-Meldrum, J. J. Cui, H. L. Dai, J. P. Dai, A. Dbeyssi, R. E. de Boer, Dmitri Dedovich, C. Q. Deng, Z. Y. Deng, A. G. Denig, I. Denisenko, M. Destefanis, F. De Mori, B. Ding, X. X. Ding, Y. Ding, Y. X. Ding, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, M. C. Du, S. X. Du, Yunyou Duan, Z. H. Duan, P. Egorov, Y. H. Fan, J. Fang, S. S. Fang, Wenxing Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, L. Feng, Qichun Feng, Y. T. Feng, M. Fritsch, C. D. Fu, J. Fu, Y. W. Fu, H. Gao, X. B. Gao, Y. Y. Gao, S. Garbolino, I. Garzia, P. T. Ge, Z. W. Ge, C. Geng, E. Gersabeck, A. Gilman, K. Götzen, J. D. Gong, Lu Gong, W. X. Gong, W. Gradl, S. Gramigna, M. Greco, M. H. Gu, Y. T. Gu, C. Y. Guan, A. Q. Guo, L. B. Guo, Ming Guo, R. P. Guo, Y. P. Guo, A. Guskov, J. Gutierrez, K. Han, T. T. Han, F. Hanisch, Kai Hao, X. Q. Hao, F. A. Harris, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, T. Holtmann, P. C. Hong, G. Y. Hou, X. T. Hou, Y. R. Hou, Z. L. Hou, H. Hu, J. F. Hu, Q. Hu, S. L. Hu, T. Hu, Y. Hu, Z. M. Hu, G. S. Huang, K. X. Huang, L. Q. Huang, P. Huang, X. T. Huang, Yanping Huang, Y. S. Huang, T. Hussain, N. Huesken, N. in der Wiesche, J. Jackson, S. Janchiv, Quan Ji, Q. P. Ji, W. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, Z. Jiao, Danli Jiang, H. B. Jiang, P. C. Jiang, S. J. Jiang, T. J. Jiang, X. S. Jiang, Y. Jiang, J. B. Jiao, J. K. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, X. M. Jing, T. Johansson, S. Kabana, N. Kalantar‐Nayestanaki, X. L. Kang, X. S. Kang, M. Kavatsyuk, B. C. Ke, V. Khachatryan, A. Khoukaz, R. Kiuchi, O. B. Kolcu, B. Kopf, M. Kuessner, X. Kui, Navneet Kumar, A. Kupść, W. Kühn, Qing Lan, W. N. Lan, T. T. Lei, M. Lellmann, T. Lenz, C. Li, C. Li, C. K. Li, Cheng Li, D. M. Li, Li Fei, Gang Li, Hai-Bo Li, H. J. Li, H. Li, Hui Li, J. R. Li, Jingshu Li, K. Li, K. L. Li, L. J. Li, Lei Li, M. H. Li, M. R. Li, Peilian Li, P. R. Li, Q. M. Li, Q. X. Li, R. Li, S. X. Li, Teng Li, T. Y. Li, W. D. Li, Weiguo Li, X. Li, X. H. Li, X. L. Li, X. Y. Li, X. Z. Li, Y. G. Li, Y. P. Li, Z. J. Li, Z. Y. Li, C. Liang, H. Liang, Y. F. Liang, Y. F. Liang, G. R. Liao, L. B. Liao, M. H. Liao, Y. P. Liao, J. Libby, A. Limphirat, C. C. Lin, C. X. Lin, D. X. Lin, L. Q. Lin, T. Lin, B. Liu, B. X. Liu, C. Liu, C. X. Liu, Fang Liu, F. H. Liu, Feng Liu, G. Liu, Hao Liu, H. Liu, H. Liu, H. M. Liu, Huihui Liu, Jianbei Liu, J. J. Liu, K. Liu, K. Y. Liu, K. Y. Liu, K. Liu, L. Liu, L. C. Liu, Lu Liu, M. H. Liu, P. Liu, Qian Liu, Shubin Liu, T. Liu, W. M. Liu, W. T. Liu, X. K. Liu, X. Y. Liu, Yuan Liu, Y. B. Liu, Zhenan Liu, Z. D. Liu, Zhiqing Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. G. Lu, X. L. Lu, Y. Lu, Yuehui Lu, Y. Lu, Z. H. Lu, C. L. Luo, J. R. Luo, J. S. Luo, M. X. Luo, T. Luo, X. L. Luo, Zheng Lv, X. R. Lyu, Y. F. Lyu, Y. H. Lyu, F. C., H. Ma, H. L., J. L., L.L. Ma, L. R., R. Q., T. Ma, X. T., X. Y. Ma, Y. Ma, F. E. Maas, I. Mackay, M. Maggiora, S. Malde, H. X. Mao, Y. J. Mao, Z. P. Mao, S. Marcello, A. M. Marshall, F. M. Melendi, Y. H. Meng, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, H. Miao, T. J. Min, R. E. Mitchell, X. H. Mo, B. Moses, N. Yu. Muchnoi, J. Muskalla, Y. Nefedov, F. Nerling, L. S. Nie, I. B. Nikolaev, Zhe Ning, S. Nisar, Q. L. Niu, W. D. Niu, C. Normand, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, Y. P. Pei, M. Pelizaeus, H. Peng, X. J. Peng, Yiyan Peng, K. Peters, K. Petridis, Jialun Ping, R. G. Ping, V. Prasad, F. Z. Qi, H. R. Qi, Ming Qi, S. Qian, W. B. Qian, Cong‐Feng Qiao, J. H. Qiao, J. J. Qin, J. L. Qin, L. Q. Qin, Lu Qin, P. B. Qin, X. P. Qin, Xiaoshuai Qin, Zhonghua Qin, J. F. Qiu, Z. H. Qu, J. H. Rademacker, C. F. Redmer, Angelo Rivetti, M. Rolo, G. Rong, S. S. Rong, F. Rosini, Ch. Rosner, M. Q. Ruan, N. Salone, A. Sarantsev, Y. Schelhaas, K. Schoenning, M. Scodeggio, K. Y. Shan, W. Shan, X. Y. Shan, Z. J. Shang, J. F. Shangguan, L. G. Shao, M. Shao, C. P. Shen, H. F. Shen, W. H. Shen, X. Y. Shen, B. A. Shi, H. Shi, J. L. Shi, Jingyan Shi, S. Y. Shi, X. Shi, Haifeng Song, J. J. Song, T. Z. Song, Y. J. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, S. Su, Y. J. Su, G. B. Sun, G. X. Sun, H. Sun, Hao-Kai Sun, J. F. Sun, K. Sun, L. Sun, S. S. Sun, T. Sun, Yu-Chang Sun, Y. H. Sun, Y. Sun, Y. Z. Sun, Z. Q. Sun, Z. T. Sun, C. J. Tang, G. Y. Tang, J. Tang, J. J. Tang, L. F. Tang, Yong Tang, L. Y. Tao, M. Tat, J. X. Teng, J. Y. Tian, W. H. Tian, Y. Tian, Z. F. Tian, I. Uman, Bo Wang, Cong Wang, D. Wang, A. Washbrook, J. Wang, K. Wang, Liangliang Wang, L. W. Wang, Meng Wang, M. Wang, N. W. Wang, S. Wang, Ting Wang, T. J. Wang, Wei Wang, Wei Wang, W. P. Wang, X. Wang, X. F. Wang, X. J. Wang, X. L. Wang, X. N. Wang, Y. F. Wang, Y. D. Wang, Yinghao Wang, Y. Wang, Y. N. Wang, Y. Q. Wang, Yaqian Wang, Yi Wang, Yuan Wang, Z. Wang, Z. L. Wang, Z. L. Wang, Z. Q. Wang, Z. Y. Wang, D. H. Wei, H. R. Wei, F. Weidner, S. P. Wen, Y. R. Wen, U. Wiedner, G. Wilkinson, M. Wolke, Chunhua Wu, J. F. Wu, L. H. Wu, L. J. Wu, L. J. Wu, Lianjie Wu, S. Wu, S. M. Wu, X. Wu, X. H. Wu, Y. J. Wu, L. Xia, X. M. Xian, B. H. Xiang, D. Xiao, G. Y. Xiao, H. Xiao, Y. L. Xiao, Zhen-Jun Xiao, C. Xie, K. J. Xie, X. H. Xie, Y. G. Xie, Y. G. Xie, Y. Xie, Z. P. Xie, Tianyu Xing, Changhua Xu, Chuangjie Xu, G. F. Xu, H. Y. Xu, M. Xu, Qingjun Xu, Q. N. Xu, T. D. Xu, W. Xu, W. L. Xu, X. P. Xu, Y. C. Xu, Z. S. Xu, F. Yan, H. Y. Yan, L. Yan, W. B. Yan, W. C. Yan, W. H. Yan, W. P. Yan, X. Q. Yan, H. J. Yang, H. L. Yang, H. X. Yang, J. H. Yang, Tao Yang, P. Yepes, Y. F. Yang, Y. Yang, Y. Q. Yang, Y. X. Yang, Y. Z. Yang, M. Ye, M. H. Ye, Z. J. Ye, J. H. Yin, Z. You, B. Yu, Chunxu Yu, G. Yu, J. Yu, M. C. Yu, Tao Yu, Xudong Yu, Y. C. Yu, C. Z. Yuan, H. Yuan, L. Yuan, S. C. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, Ying Yue, A. A. Zafar, S. H. Zeng, X. Zeng, Y. Zeng, Yujie Zeng, Y. J. Zeng, X. Y. Zhai, Y. H. Zhan, A. Q. Zhang, B. L. Zhang, B. X. Zhang, D. H. Zhang, G. Y. Zhang, Jinlong Zhang, H. Zhang, H. Zhang, Hangchang Zhang, H. H. Zhang, Huaqiao Zhang, H. R. Zhang, Hongyu Zhang, Jin Zhang, Jin Zhang, J. J. Zhang, Jielei Zhang, Jingqing Zhang, J. S. Zhang, Jiawen Zhang, J. X. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, L. Zhang, Lei Zhang, N. Zhang, P. Zhang, Q. Zhang, Q. Y. Zhang, R. Y. Zhang, Shuihan Zhang, Shulei Zhang, X. M. Zhang, X. Y Zhang, X. Zhang, Y. T. Zhang, Yinhong Zhang, Y. M. Zhang, Zhengde Zhang, Z. H. Zhang, Z. X. Zhang, Zh. Zh. Zhang, Guang Zhao, J. Y. Zhao, J. Zhao, Ling Zhao, Lei Zhao, M. G. Zhao, N. Zhao, R. P. Zhao, Shujun Zhao, Yubin Zhao, Y. L. Zhao, Y. X. Zhao, Z. Zhao, A. Zhemchugov, B. Zheng, B. M. Zheng, J. P. Zheng, W. J. Zheng, Y. Zheng, B. Zhong, C. Zhong, H. Zhou, J. Q. Zhou, J. Y. Zhou, S. Zhou, Xiang Zhou, X. Zhou, X. R. Zhou, X. Y. Zhou, Y. Zhou, Y. Z. Zhou, A. N. Zhu, J. Zhu, K. J. Zhu, Kejun Zhu, K. Zhu, L. Zhu, L. Z. Zhu, S. H. Zhu, T. J. Zhu, W. D. Zhu, W. J. Zhu, W. Z. Zhu, Y. C. Zhu, Zian Zhu, X. Zhuang, J. H. Zou, Jean W. Zu

Bibliographic record

VenueJournal of High Energy Physics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsInstitute of Particle Physics
FundersShanghai Key Laboratory for Particle Physics and CosmologyCAS Center for Excellence in Particle PhysicsAkasaki Institute, Nagoya UniversityOverseas Expertise Introduction Center for Discipline Innovation of Food Nutrition and Human Health (111 Center)Natural Science Foundation of Gansu ProvinceVetenskapsrådetFundamental Research Funds for the Central UniversitiesNarodowe Centrum NaukiChinese Academy of SciencesNational Natural Science Foundation of ChinaKnut och Alice Wallenbergs StiftelseNational Key Research and Development Program of ChinaStrongNational Research FoundationIstituto Nazionale di Fisica NucleareDeutsche ForschungsgemeinschaftNational Research Foundation of KoreaInstitute of High Energy PhysicsU.S. Department of Energy
KeywordsCross section (physics)Branching fractionLuminosityCollisionDetectorResonance (particle physics)Electron–positron annihilation

Abstract

fetched live from OpenAlex

A bstract Using e + e − collision data corresponding to a total integrated luminosity of 20 fb − 1 collected with the BESIII detector at the BEPCII collider, we present a measurement of the Born cross section for the process $$ {e}^{+}{e}^{-}\to p{K}^{-}{K}^{-}{\overline{\Xi}}^{+} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>e</mml:mi> <mml:mo>+</mml:mo> </mml:msup> <mml:msup> <mml:mi>e</mml:mi> <mml:mo>−</mml:mo> </mml:msup> <mml:mo>→</mml:mo> <mml:mi>p</mml:mi> <mml:msup> <mml:mi>K</mml:mi> <mml:mo>−</mml:mo> </mml:msup> <mml:msup> <mml:mi>K</mml:mi> <mml:mo>−</mml:mo> </mml:msup> <mml:msup> <mml:mover> <mml:mi>Ξ</mml:mi> <mml:mo>¯</mml:mo> </mml:mover> <mml:mo>+</mml:mo> </mml:msup> </mml:math> at 39 center-of-mass energies between 3.5 and 4.9 GeV with a partial reconstruction technique. By performing a fit to the dressed cross section of $$ {e}^{+}{e}^{-}\to p{K}^{-}{K}^{-}{\overline{\Xi}}^{+} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>e</mml:mi> <mml:mo>+</mml:mo> </mml:msup> <mml:msup> <mml:mi>e</mml:mi> <mml:mo>−</mml:mo> </mml:msup> <mml:mo>→</mml:mo> <mml:mi>p</mml:mi> <mml:msup> <mml:mi>K</mml:mi> <mml:mo>−</mml:mo> </mml:msup> <mml:msup> <mml:mi>K</mml:mi> <mml:mo>−</mml:mo> </mml:msup> <mml:msup> <mml:mover> <mml:mi>Ξ</mml:mi> <mml:mo>¯</mml:mo> </mml:mover> <mml:mo>+</mml:mo> </mml:msup> </mml:math> with a power law function for continuum production and one resonance at a time for the ψ (3770), ψ (4040), ψ (4160), ψ (4230), ψ (4360), ψ (4415) or ψ (4660), respectively, the upper limits for the product of partial electronic width and branching fraction into the final state $$ p{K}^{-}{K}^{-}{\overline{\Xi}}^{+} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> <mml:msup> <mml:mi>K</mml:mi> <mml:mo>−</mml:mo> </mml:msup> <mml:msup> <mml:mi>K</mml:mi> <mml:mo>−</mml:mo> </mml:msup> <mml:msup> <mml:mover> <mml:mi>Ξ</mml:mi> <mml:mo>¯</mml:mo> </mml:mover> <mml:mo>+</mml:mo> </mml:msup> </mml:math> for these resonances are determined at the 90% confidence level.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.297
Teacher spread0.277 · 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 teacher head, 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".

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Citations1
Published2025
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