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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
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This study introduces a system to recommend missing Wikipedia articles, boosting editor engagement and article creation. Personalized recommendations enhance Wikipedia

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Area of Science:

  • Computational Linguistics
  • Information Science
  • Digital Humanities

Background:

  • Wikipedia language editions exhibit significant disparities in content comprehensiveness.
  • Information is fragmented across different language versions, with most editions containing only a fraction of the total knowledge available across all Wikipedias.

Purpose of the Study:

  • To develop and evaluate an end-to-end system for identifying and recommending articles that exist in one Wikipedia language edition but are missing in another.
  • To address the challenge of incomplete article coverage across diverse language Wikipedias.

Main Methods:

  • An end-to-end system was designed to identify missing articles, rank them by importance, and personalize recommendations to editors based on their interests.
  • A controlled experiment involving 12,000 French Wikipedia editors was conducted to validate the system's effectiveness.

Main Results:

  • Personalized article recommendations doubled editor engagement.
  • The likelihood of a missing article being created increased by a factor of 3.2 due to recommendations.
  • Articles created via recommendations were of comparable quality to organically created articles.

Conclusions:

  • The developed system effectively increases editor engagement and accelerates Wikipedia's growth without compromising content quality.
  • Personalized recommendations are a viable strategy for improving cross-lingual knowledge sharing and content completeness on Wikipedia.