Extracts key metadata and performs comprehensive technical checks on manuscripts and accompanying documents to identify missing elements, incomplete metadata, and adherence to journal guidelines.
An AI model trained on STM content that uses sentence structure and parts of speech attributes to assess the language quality of a manuscript, provide a score and deliver a document with language feedback.
Dictionary specifically for STM content that recognises and highlights typos, incorrect spelling, and grammatical inconsistencies, providing accurate recommendations and suggestions.
Identifies optimal break-points for long and complex mathematical equations with over 90% accuracy, helping pagination engines and web pages recognise where to insert logical line breaks.
RNN ML-model for structuring references is coupled with validation against established databases and CSL based styling. With high automation levels of over 96% and accurate error awareness, the product generates significant production efficiency.