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48match
kylemcnease.com
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3 co-citations2 shared tech1 shared categoryscience
46match
georgelandon.com
George V. Landon — Bio
2 co-citations2 shared tech2 shared categoryscience
44match
dianewoodbridge.com
Diane Woodbridge, Ph.D
2 co-citations3 shared tech2 shared categoryscience
43match
craighilllab.com
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3 co-citations1 shared tech1 shared categoryscience
43match
devleenasamanta.com
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0 co-citations3 shared tech1 shared categorybiological-sciences
42match
adrianobarra.com
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1 co-citations2 shared tech2 shared categoryscience
41match
apokalypsis.com
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1 co-citations2 shared tech1 shared categorybiological-sciences
40match
julielmcdonald.com
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3 co-citations1 shared tech1 shared categorybiological-sciences
40match
hofstragroup.com
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0 co-citations2 shared tech1 shared categoryphysics
40match
bond-lab.com
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0 co-citations2 shared tech1 shared categoryscience
40match
jiachengmiao.com
Jiacheng's website
3 co-citations2 shared tech2 shared categoryscience
39match
mariakleshnina.com
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1 co-citations2 shared tech1 shared categoryscience
38match
jeffnivala.com
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2 co-citations1 shared tech1 shared categoryscience
37match
manaswikondapally.com
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0 co-citations2 shared tech1 shared categoryphysics
37match
eliaskammoun.com
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0 co-citations2 shared tech1 shared categoryphysics
36match
boltdigitalindia.com
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1 co-citations2 shared tech1 shared categoryscience
36match
hoipolloi.io
The Hoi Polloi Lab
1 co-citations3 shared tech1 shared categorybiological-sciences
36match
devonclautice.com
Devon Clautice
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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.