A Chrome extension for researchers
Understand why it’s cited without leaving the paper.
Stop opening dozens of tabs just to check a reference. Right-click any citation to see why the authors cited it, what role it plays in the argument, and what the original research found, right in your side panel.
Coming soon to the Chrome Web Store · 5 free analyses every month
Interactive preview
Instant context right where you are reading.
When you run across a citation mid-paragraph, you shouldn’t have to break your focus and search through another paper. Right-click the reference and WhyCited breaks down why it was cited, what evidence supports it, and how it relates to the surrounding argument.
Quarterly Review of Work & Organisation · Vol. 18 (3)
Autonomy, trust and engagement in distributed research teams
S. Marchetti · J. Okonkwo · L. Devine
2. Literature review
Interest in employee autonomy has grown alongside the shift to distributed work. Prior studies report a positive association between perceived autonomy and engagement (Okafor & Lindqvist, 2021), although the strength of that association appears to vary across sectors. Fewer studies have examined how trust moderates this relationship in fully remote teams, and the evidence that exists is largely cross-sectional.
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Explain why this research is relevant
Perceived autonomy and work engagement: evidence from a cross-sector survey
Okafor, A. · Lindqvist, M. · 2021
Why it is relevant
Cited as supporting evidence that employee autonomy correlates with higher engagement. The cited study reports a positive correlation across six industries, directly reinforcing the claim in this literature review.
Citation role
- Supports
- Contextualises
Current paper’s use
Establishes the link between autonomy and engagement as foundational background before introducing trust as a moderator.
Linked paper’s contribution
Reports a statistically significant positive relationship between autonomy and engagement (r = .41, p < .001) across 2,414 survey respondents.
Evidence available
- Current paper
- Citation context + metadata
- Linked paper
- Abstract only
Confidence: Moderate
Key evidence
Current paper: Literature review
“Prior studies report a positive association between perceived autonomy and engagement (Okafor & Lindqvist, 2021), although the strength of that association appears to vary across sectors.”
Linked paper: Abstract
“Across sectors, perceived autonomy showed a moderate positive association with work engagement (r = .41, p < .001).”
Limitations
- The full text for the cited paper is paywalled. This assessment is based on the published abstract.
How it works
From citation to context in three steps.
Right-click any citation
When reading an academic paper in Chrome, right-click a reference link—or select a citation marker that is not linked—and choose “Explain why this research is relevant”.
WhyCited gathers the context
We identify the cited paper and gather available open-access text, abstracts, or metadata, without bypassing paywalls.
Read the explanation in your sidebar
A side panel breaks down why the paper was cited in that specific passage, what it contributes, and how much source evidence was available.
Evidence transparency
Every answer shows the evidence behind it.
Generic AI tools often sound confident even when they have only read a paper’s title. WhyCited grades every explanation by what it could actually access and states its sources clearly.
Confidence levels (high, moderate, or low) reflect real source availability and the clarity of the citation’s role. If only an abstract was available, WhyCited tells you upfront.
The four access levels
- Full text
The full paper is openly accessible. The analysis can quote and evaluate specific passages.
- Abstract only
The abstract is public, but the body is paywalled. The summary is drawn from the abstract, with confidence calibrated accordingly.
- Metadata only
Title, authors, journal, and references. The citation's role is cautiously inferred from bibliographic details.
- Unavailable
No public record could be retrieved. WhyCited states this directly instead of guessing.
Pricing
Plans for every reading workflow.
Every plan includes evidence-graded summaries. Upgrade for higher monthly volume or deep analysis for complex, ambiguous citations.
Free
£0
For exploring WhyCited in your daily reading workflow.
- 5 standard analyses / month
- No deep analyses
- No auto-escalation
Starter
£3.99/mo
For coursework, thesis writing, and consistent reading.
- 200 standard analyses / month
- No deep analyses
- No auto-escalation
Pro
Most popular£7.99/mo
For active researchers who need deeper analysis on complex papers.
- 500 standard analyses / month
- 50 deep analyses / month
- Hard cases auto-escalate to deep analysis
Lab
£15.99/mo
For intensive literature reviews and large-scale synthesis.
- 1,500 standard analyses / month
- 150 deep analyses / month
- Hard cases auto-escalate to deep analysis
Deep analysis uses Anthropic Claude to examine ambiguous citations, conflicting claims, or complex methodology. Standard analyses use Google Gemini for fast evaluation of straightforward references.
FAQ
Frequently asked questions
Does it bypass paywalls?
No. WhyCited retrieves only openly accessible content and public metadata from sources such as Crossref, arXiv, and open-access repositories. When a paper is paywalled, WhyCited bases its analysis on the abstract and metadata, noting this clearly in the results.
What data does the extension send?
Nothing leaves your browser until you choose to analyse a citation. When you right-click, the extension sends only the necessary context: the citation link or selected marker, a matching bibliography entry where needed, the surrounding sentence and paragraph, the section heading, and page metadata. It never accesses your browsing history, cookies, or other open tabs.
Does it work on PDFs?
HTML articles across journal sites, arXiv, and open repositories work best. Because Chrome limits what extensions can access inside its built-in PDF viewer, PDF analysis currently relies on the document URL and available metadata. Direct PDF extraction is actively in development.
Which AI models does it use?
Standard analyses use Google Gemini for fast summaries of straightforward citations. Deep analyses use Anthropic Claude for nuanced reasoning on complex or ambiguous claims. All model processing runs securely on our backend, so API keys never touch the browser extension.
Do I need an account?
Yes. An account connects your browser extension to your monthly allowance, including the 5 free analyses on the Free plan. You can sign up in seconds with a magic email link.
Stay in the flow of what you’re reading.
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