U-100 29G 1ml/cc 1/2" (12.7mm) Box of 100
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Review Analysis Results
Analysis Summary
The review set shows mixed authenticity signals. Positive aspects include: natural language variation, specific medical use cases (insulin, GLP-1), and legitimate negative reviews with detailed complaints about needle quality and functionality. However, concerning patterns include: high proportion of 5-star reviews (7/14), several overly generic positive reviews lacking substance ('works fine', 'Very good quality! No issues'), and some reviews that focus excessively on shipping/packaging rather than product performance. The presence of verified purchase tags (V) adds credibility, but the generic nature of some positive reviews and the polarized rating distribution (mostly 5-star and 1-star) suggest potential manipulation. The moderate fake percentage reflects that while many reviews appear genuine, there's likely some artificial boosting of positive ratings.
Review Statistics
About Review Data Collection
We extract as much review data as Amazon makes available at the time of analysis. The amount may vary due to Amazon's rate limiting, regional restrictions, or other factors. Our analysis is based on the reviews we successfully collected.
Want to analyze more reviews? Install the Null Fake Chrome extension to capture and analyze additional reviews as you browse Amazon.
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Price Analysis
Price analysis pending
Price insights will be available shortly.
Understanding This Analysis
What does Grade C mean?
This product has moderate review authenticity concerns. A notable portion of reviews show suspicious patterns. Consider reading reviews carefully before purchasing.
Adjusted Rating Explained
The adjusted rating (3.20 stars) represents what we estimate this product's rating would be if fake reviews were removed. This product's adjusted rating is lower than Amazon's displayed rating (3.71 stars), suggesting positive fake reviews may be inflating the score.
How We Detect Fake Reviews
Our AI analyzes multiple factors: language patterns (generic vs. specific), reviewer behavior (history, timing), temporal anomalies (review clusters), verification status, sentiment authenticity, and statistical outliers. No single factor determines a review is fake - we look at the combination of signals.
Important Limitations
No automated system is perfect. Sophisticated fake reviews can evade detection, and some genuine reviews may be incorrectly flagged. Use this analysis as one data point in your purchasing decision, not the only factor. Reading actual review content yourself is always valuable.
