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Predicting highly cited papers: : A Method for Early Detection of Candidate Breakthroughs

  • Autores: Ilya V. Ponomarev, Duane E. Williams, Charles J. Hackett, Joshua D. Schnell, Laurel L. Haak
  • Localización: Technological Forecasting and Social Change, ISSN-e 1873-5509, Vol. 81, Nº. 1, 2014, págs. 49-55
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • Scientific breakthroughs are rare events, and usually recognized retrospectively. We developed methods for early detection of candidate breakthroughs, based on dynamics of publication citations and used a quantitative approach to identify typical citation patterns of known breakthrough papers and a larger group of highly cited papers. Based on these analyses, we proposed two forecasting models that were validated using statistical methods to derive confidence levels. These findings can be used to inform research portfolio management practices.


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