sbrl (R package): papers linking to it

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to sbrl (R package) (https://CRAN.R-project.org/package=sbrl), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

4 papers in the tracked journals link to sbrl (R package) in their Crossref records, the first in 2018; most of them (1) in 2023.
By category: AI (3) and Operations Research (1); the journals with the most are Data Mining and Knowledge Discovery (2), Mathematical Programming Computation (1) and Artificial Intelligence Review (1).

By year#

20182023

Papers linking to sbrl (R package) by publication year
Year	Papers
2018	1
2020	1
2022	1
2023	1

Journals#

Journals whose papers link to sbrl (R package) most
Journal	Papers
Data Mining and Knowledge Discovery	2
Mathematical Programming Computation	1
Artificial Intelligence Review	1

Papers linking to sbrl (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2023-06-03	Benchmarking and survey of explanation methods for black box models	Data Mining and Knowledge Discovery	Francesco Bodria, Fosca Giannotti, Riccardo Guidotti et al.	277	cites it
2020-06-04	CHIRPS: Explaining random forest classification	Artificial Intelligence Review	Julian Hatwell, Mohamed Medhat Gaber, Raja Muhammad Atif Azad	101	cites it
2018-09-05	Learning customized and optimized lists of rules with mathematical programming	Mathematical Programming Computation	Cynthia D Rudin, Şeyda Ertekin	49	cites it
2022-11-14	Stable and actionable explanations of black-box models through factual and counterfactual rules	Data Mining and Knowledge Discovery	Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri et al.	39	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). sbrl (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-sbrl

@misc{scholar4ai-code-cran-sbrl,
  author = {{Scholar4AI}},
  title = {sbrl (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-sbrl}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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