{
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    {
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      "year": "2023"
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  "authors": [
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      "orcid": "0000-0001-7147-3348", 
      "affiliations": [
        {
          "country": "Japan", 
          "value": "RIKEN Nishina Center, Wako, Japan"
        }, 
        {
          "country": "China", 
          "value": "School of Physical Science and Technology, Southwest University, Chongqing, China"
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      ], 
      "surname": "Yang", 
      "given_names": "Zu-Xing", 
      "full_name": "Yang, Zu-Xing"
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    {
      "surname": "Fan", 
      "given_names": "Xiao-Hua", 
      "affiliations": [
        {
          "country": "China", 
          "value": "School of Physical Science and Technology, Southwest University, Chongqing, China"
        }, 
        {
          "country": "Japan", 
          "value": "RIKEN Nishina Center, Wako, Japan"
        }
      ], 
      "full_name": "Fan, Xiao-Hua", 
      "orcid": "0000-0002-4591-0118", 
      "email": "fanxiaohua@swu.edu.cn"
    }, 
    {
      "affiliations": [
        {
          "country": "China", 
          "value": "School of Physical Science and Technology, Southwest University, Chongqing, China"
        }
      ], 
      "surname": "Li", 
      "given_names": "Zhi-Pan", 
      "full_name": "Li, Zhi-Pan"
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    {
      "affiliations": [
        {
          "country": "Japan", 
          "value": "RIKEN Nishina Center, Wako, Japan"
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      "surname": "Nishimura", 
      "given_names": "Shunji", 
      "full_name": "Nishimura, Shunji"
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  "titles": [
    {
      "source": "Elsevier", 
      "title": "A neural network approach for orienting heavy-ion collision events"
    }
  ], 
  "collections": [
    {
      "primary": "Physics Letters B"
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  "publication_info": [
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      "journal_volume": "848 C", 
      "journal_title": "Physics Letters B", 
      "material": "article", 
      "artid": "138359", 
      "year": 2023
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  "abstracts": [
    {
      "source": "Elsevier", 
      "value": "A convolutional neural network-based classifier is elaborated to retrace the initial orientation of deformed nucleus-nucleus collisions by integrating multiple typical experimental observables. The isospin-dependent Boltzmann-Uehling-Uhlenbeck transport model is employed to generate data for random orientations of ultra-central uranium-uranium collisions at <math><msub><mrow><mi>E</mi></mrow><mrow><mtext>beam</mtext></mrow></msub><mo>=</mo><mn>1</mn><mspace width=\"0.2em\"></mspace><mtext>GeV/nucleon</mtext></math>. Statistically, the data-driven polarization scheme is essentially accomplished via the classifier, whose distinct categories filter out specific orientation-biased collision events. This will advance the deformed nucleus-based studies on nuclear symmetry energy, neutron skin, etc."
    }
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