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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "llmclean" in publications use:'
type: software
license: GPL-3.0-only
title: 'llmclean: LLM-Assisted Data Cleaning with Multi-Provider Support'
version: 0.1.1
doi: 10.32614/CRAN.package.llmclean
abstract: 'Detects and suggests fixes for semantic inconsistencies in data frames
  by calling large language models (LLMs) through a unified, provider-agnostic interface.
  Supported providers include ''OpenAI'' (''GPT-4o'', ''GPT-4o-mini'') <https://platform.openai.com>,
  ''Anthropic'' (''Claude'') <https://www.anthropic.com>, ''Google'' (''Gemini'')
  <https://ai.google.dev>, ''Groq'' (free-tier ''LLaMA'' and ''Mixtral'') <https://groq.com>,
  and local ''Ollama'' models <https://ollama.com>. The package identifies issues
  that rule-based tools cannot detect: abbreviation variants, typographic errors,
  case inconsistencies, and malformed values. Results are returned as tidy data frames
  with column, row index, detected value, issue type, suggested fix, and confidence
  score. An offline fallback using statistical and fuzzy-matching methods is provided
  for use without any application programming interface (API) key. Interactive fix
  application with human review is supported via ''apply_fixes()''. Methods follow
  de Jonge and van der Loo (2013) <https://cran.r-project.org/doc/contrib/de_Jonge+van_der_Loo-Introduction_to_data_cleaning_with_R.pdf>
  and Chaudhuri et al. (2003) <https://doi.org/10.1145/872757.872796>.'
authors:
- family-names: Islam
  given-names: Sadikul
  email: sadikul.islamiasri@gmail.com
  orcid: https://orcid.org/0000-0003-2924-7122
- family-names: Kaushal
  given-names: Rajesh
repository: https://sadikulislamiasri-hub.r-universe.dev
commit: 03c9478b9ff1f61b55ad539f936e09675ec728b3
date-released: '2026-06-01'
contact:
- family-names: Islam
  given-names: Sadikul
  email: sadikul.islamiasri@gmail.com
  orcid: https://orcid.org/0000-0003-2924-7122