Versione italiana completata meccanicamente, con struttura inglese originale conservata; revisione umana consigliata.
You Think "Real" Is Enough?
In academic writing, the most overlooked step is citation verification.
In the past, the only question was: Does this paper actually exist? The rise of ChatGPT made "hallucinated citations" a hot topicโAI can fabricate references that look perfect but don't exist.
LitSource's first-generation verification addressed this: detecting whether a citation is real, whether the DOI matches, and whether the metadata is correct.
But after serving thousands of biomedical users, we realized: "Real" is just the baseline. "Safe to cite" is where the real danger lies.
A citation can be 100% real and still cause serious problems:
- The paper has been retracted due to fraud
- The paper is only a preprintโnever peer-reviewed
- The paper is a narrative review, but you cited it as primary evidence
- The paper is an animal study, but you used it to support a clinical conclusion
- The paper has a published erratum, and the data you cited may have changed
The worst part? Reviewers catch these instantly. You might not even know.
Citation Risk Radar: Your Last Safety Net
This is why we built the Citation Risk Radar.
It goes beyond true/false detection. On top of verifying authenticity, it performs a comprehensive risk scan for every citation and provides clear risk levels with actionable recommendations.
Six Risk Detection Dimensions
| Risk Type | Level | Meaning |
|---|---|---|
| ๐ด Retracted | Critical | Paper withdrawn due to misconductโmust remove |
| ๐ด Expression of Concern | High | Journal has raised formal concerns |
| ๐ Preprint Only | High | Not peer-reviewed, unsuitable as core evidence |
| ๐ Animal / In vitro Only | High* | High risk when supporting clinical claims |
| ๐ก Review, Not Primary | Medium | Reviews are not original research |
| ๐ก Erratum / Correction | Medium | Verify whether corrections affect your cited data |
Five-Level Risk Classification
Every citation is classified into a clear risk level:
- ๐ด Critical โ e.g., retracted; must remove immediately
- ๐ High โ e.g., preprint, animal-only; not recommended for direct citation
- ๐ก Medium โ e.g., review, erratum; requires manual review
- ๐ข Low โ no known risks; safe to cite
- ๐ต Info โ informational note; no material impact
Complete Risk Report Per Citation
For each reference, the system provides:
- Risk Name โ e.g., "Retracted"
- Risk Level โ e.g., Critical
- Risk Evidence โ e.g., "Listed in Retraction Watch; author had 90+ papers retracted for data fabrication"
- Recommended Action โ e.g., "Remove this citation; search for a non-retracted RCT with the same PICO"
Evidence Level Tags
Beyond risk detection, the Risk Radar labels each reference with its position in the evidence pyramid:
- ๐ต Guideline โ Clinical practice guideline (highest level)
- ๐ต Meta-Analysis โ Pooled analysis of multiple studies
- ๐ต Systematic Review โ Structured evidence synthesis
- ๐ข RCT โ Randomized controlled trial
- ๐ก Cohort โ Cohort study
- ๐ก Case-Control โ Case-control study
- ๐ Animal Study โ Animal model research
- ๐ In vitro โ Cell/tissue experiments
- ๐ฃ Review โ Narrative review (not systematic)
- โช Case Report โ Individual case description
The system also tags the subject level: Human / Animal / In vitro, helping you instantly determine whether the evidence matches your clinical claim.
Actionable Recommendations
The Risk Radar doesn't just labelโit tells you exactly what to do:
| Recommendation | Meaning |
|---|---|
| โ Safe to cite | No risk, evidence level matches, use with confidence |
| ๐ Background only | Suitable for Introduction, not for Discussion conclusions |
| ๐ Mechanism support only | Animal/in vitro results for mechanistic context only |
| โ ๏ธ Consider replacing | Higher-level evidence is available |
| ๐ Manual review needed | Erratum or partial mismatch; verify manually |
| ๐ซ Must remove | Retracted or critically compromised; do not cite |
Real-World Use Cases
๐ Pre-Submission Check
Before hitting "Submit," paste your reference list into Risk Radar for a final scan. Catch retracted or high-risk citations before the reviewers do.
๐ค AI-Generated Reference QA
If you used ChatGPT, Claude, or Kimi to generate references, run them through Risk Radar. AI tools may recommend papers that are retracted or don't exist.
๐ Systematic Review Screening
When writing a systematic review with 100+ references, Risk Radar quickly filters out reviews, animal studies, and preprints that shouldn't serve as core evidence.
๐ Grant and Ethics Writing
Citations in grant applications and IRB materials must be bulletproof. Risk Radar ensures every reference is verified, risk-free, and traceable.
โ๏ธ Revision Response
When reviewers request additional citations, new references need the same level of scrutiny. Risk Radar prevents introducing new citation risks during revision.
Why Biomedical Only
Biomedical research has a far lower tolerance for citation errors than other fields. A retracted paper in a clinical decision chain can affect treatment protocols and patient safety.
Citation Risk Radar is purpose-built for biomedical contexts:
- Leverages PubMed PublicationType and MeSH terms for study classification
- Uses Crossref and Retraction Watch for retraction and erratum detection
- Explicitly distinguishes human studies from animal/in vitro research
- Risk levels align with the clinical evidence pyramid
We don't do generic, cross-discipline checking. We do deep biomedical evidence risk control.
In One Sentence
Citation Risk Radar: It doesn't just tell you if a reference is realโit tells you if it's safe to cite.
Three minutes before submission. One complete risk check for your entire reference list.
