A free bibliometric screening tool for editors, publishers, and researchers. Enter an author's OpenAlex ID and the index calculates automatically from public data. Developed by Dr. Mina T. Kelleni, Minia University, Egypt.
ARI² combines four public-record signals into a composite score. High scores flag statistically unusual publication patterns warranting human review — not automatic conclusions of misconduct. Validated in a retrospective pilot study of 28 authors. Always apply the due-process checklist before drawing any conclusion.
Choose automatic lookup (recommended) to let the tool fetch all data directly from OpenAlex, or enter values manually if you already have them.
Type the author's name to find their OpenAlex profile. The tool will automatically retrieve all values needed for ARI² — including co-authors and retractions — directly from OpenAlex.
Search for an author and click "Fetch Data and Calculate ARI²" to see results.
Enter all values and click Calculate to see the ARI² score.
The automatic lookup handles all data retrieval for you. The guide below explains how to find the OpenAlex Author ID and how to obtain co-author and retraction data manually if you prefer the manual entry mode.
In the Automatic Lookup tab of the calculator above, type the author's full name and click Search. The tool searches OpenAlex and returns matching author profiles.
Click on the matching author. Verify by checking the institution, field, and country. Multiple authors with the same name may appear — select the one whose profile matches the author you are assessing.
If the correct author does not appear in the results, try a different spelling, add the institution name, or use the Manual Entry mode with values obtained directly from openalex.org.
The tool automatically retrieves the author's full works list from OpenAlex, counts unique co-authors across all publications, counts retracted works, and calculates all four signals and the composite ARI² score. A progress bar shows the status for authors with large publication records.
What is computed automatically: Works count, Citations, h-index — from the author profile. Unique co-authors — by collecting all co-author IDs across all works and counting each person once. Retractions — by counting works where OpenAlex has flagged is_retracted = true.
No downloads, no exports, no manual counting needed.
Search for the author by name on openalex.org. Select Authors in the category filter. Click the correct profile and verify using institution and field.
The unique co-author count is not displayed directly on the author profile page. It requires fetching the author's works data. The simplest method: copy the author ID from the page URL (the part starting with A followed by digits), then use the following API call in your browser address bar.
Easier alternative: Use the Automatic Lookup mode. It performs this entire process for you and shows the co-author count before calculating the score.
Automatic Lookup is strongly recommended for all users.
The Automatic Lookup mode detects retractions from OpenAlex's is_retracted field, which is the same source used in the original ARI² research. OpenAlex's retraction detection is not exhaustive — some retractions are indexed later than others. Retraction Watch is the most comprehensive retraction database and should be used to cross-check the result for high-stakes editorial assessments.
When to cross-check with Retraction Watch: When the automatic lookup returns a non-zero retraction count and you need to verify the exact number. When the automatic lookup returns zero but you have reason to suspect retractions exist. Before taking any formal editorial action based on a High score band result.
For routine screening, OpenAlex retraction data is sufficient. For formal proceedings, always verify against Retraction Watch.
Visit retractionwatch.com/retraction-watch-database and search by the author's full name. Count the total retracted papers listed. If a discrepancy exists between OpenAlex and Retraction Watch, use the higher count and enter it manually using the Manual Entry mode.
ARI² scores are calibrated against the 28-author pilot cohort. Score bands are exploratory heuristics — not validated cut-offs. Every flag requires human review and contextual assessment before any decision is taken.
Calibration caveat: Scores are normalized against the 28-author pilot cohort (Kelleni 2026) and are not yet externally validated. Authors whose profiles fall outside the pilot range may receive scores below 0 or above 100 — these should be read qualitatively. For the full open-source scoring pipeline, see the Zenodo repository. A validated reference population is under development.
Any author receiving a Moderate or High score band flag must be reviewed against this checklist before any editorial action is taken. ARI² is a screening aid — the beginning of an inquiry, not its conclusion.
Confirm via ORCID. Name disambiguation errors in OpenAlex can inflate co-author counts for authors with common names.
Is high co-author count normal in this field? Large consortium science and clinical trial networks legitimately produce high Signal A values.
Is the author early-career? High output may reflect a productive lab. Is the elevated signal recent or consistent across the full career?
Are retractions from a single event or distributed across multiple journals and years? The pattern matters as much as the count.
Do co-authors appear across many unrelated papers? Are many one-time collaborators from geographically and institutionally unconnected locations?
Were many papers submitted to the same journal cluster or known predatory publishers? Unusual special-issue clustering warrants scrutiny.
ARI² flags trigger full investigation — never automatic rejection. All decisions must follow institutional due-process procedures and allow the author to respond.
ARI² scores are probabilistic risk indicators, not determinations of misconduct. A high score reflects a statistically unusual publication pattern that warrants human review and contextual investigation — not automatic sanction. No author should face rejection, retraction, defunding, or any professional consequence based solely on an ARI² score. The index is a screening aid. Misuse of this index to make adverse decisions without adherence to due process would be both ethically unsound and legally perilous.
This tool uses only publicly available bibliometric data from OpenAlex and the Retraction Watch Database. No human subjects are recruited, contacted, or experimented upon. Named case authors in the validation study were identified exclusively through documented public records. The due-process framework reflects the author's commitment to responsible and proportionate use of bibliometric risk indicators.
This website is available under CC BY 4.0. The underlying code and dataset are available under Apache 2.0 via the Zenodo repository.
To cite: Kelleni MT. Commercial authorship and content fraud leave distinct bibliometric signatures: a retrospective feasibility study of the Author Research Integrity Risk Index (ARI²). Preprint, 2026.
Zenodo Repository