By creating crowd-sourcing tasks that can be easily posted and results retrieved using Amazon's Mechanical Turk (MTurk) API, researchers can use this solution to validate the quality of topics obtained from unsupervised or semi-supervised learning methods, and the relevance of topic labels assigned. This helps ensure that the topic modeling results are accurate and useful for research purposes. See Ying and others (2022) <doi:10.1101/2023.05.02.538599>. For more information, please visit <https://github.com/Triads-Developer/Topic_Model_Validation>.

Generate suggestions for validation rules 
  from a reference data set, which can be used as a starting point for domain specific 
   rules to be checked with package 'validate'.

Rule sets with validation rules may contain redundancies or contradictions. 
  Functions for finding redundancies and problematic rules are provided, 
  given a set a rules formulated with 'validate'.

Many bioacoustic data workflows rely on manual review (i.e., 
    validation) of a subset of call files to provide information to statistical
    models that account for misclassification by automated algorithms.
    Because manual review can be prohibitively expensive, simulation can be a 
    valuable tool to aid the design of studies that use validation. This package 
    provides user-friendly functions to reduce the programming burden of 
    simulation studies that compare validation sampling designs. Simulations 
    assume the count-detection model, which is a realistic model for bioacoustic 
    data, especially for bats. For more information, see Oram et al. (2025) 
    <doi:10.1214/25-AOAS2096>.

Given a partition resulting from any clustering algorithm, the implemented tests allow valid post-clustering inference by testing if a given variable significantly separates two of the estimated clusters. 
             Methods are detailed in: Hivert B, Agniel D, Thiebaut R & Hejblum BP (2022). 
             "Post-clustering difference testing: valid inference and practical considerations", <arXiv:2210.13172>.