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87match
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79match
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1 co-citations4 shared tech2 shared categoryfiction
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1 co-citations4 shared tech2 shared categorybooks-and-literature
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1 co-citations4 shared tech2 shared categorybooks-and-literature
72match
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1 co-citations4 shared tech2 shared categoryfiction
71match
joannevaliukas.com
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71match
makilien.com
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1 co-citations4 shared tech2 shared categorybooks-and-literature
71match
jejack.com
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1 co-citations4 shared tech2 shared categoryfiction
71match
adriandebeer.com
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1 co-citations4 shared tech2 shared categorybooks-and-literature
70match
gennigunn.com
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1 co-citations0 shared tech2 shared categorybooks-and-literature
69match
juliaphillipswrites.com
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1 co-citations4 shared tech2 shared categorybooks-and-literature
69match
elcidsbooks.com
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1 co-citations4 shared tech2 shared categorybooks-and-literature

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.