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Mechanisms of Pathogenicity | Or the war between two genomes — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Infectious Diseases →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
eshraghilab.org ↗	66 match 1 shared topics	Eshraghi Lab - Bacterial pathogenesis research @ University of Florida	en	infectious-diseases Wix	robots llmsaihumans	emailphone	none
bunker-bytes.com ↗	64 match 1 shared topics	Bunker Bytes – Conversations with myself during the COVID-19 outbreak in the UK	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
stamatakilab.com ↗	64 match 1 shared topics	Stamataki Lab \| Liver Immunology and Virology Laboratory at the University of Birmingham, UK	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
coronavirus.gov ↗	63 match 1 shared topics	Lab Leak: The True Origins of Covid-19 – The White House	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
covid.gov ↗	63 match 1 shared topics	Lab Leak: The True Origins of Covid-19 – The White House	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
covidtests.gov ↗	63 match 1 shared topics	Lab Leak: The True Origins of Covid-19 – The White House	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
visualizingthevirus.com ↗	63 match 1 shared topics	Visualising the Virus	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
factsnotfearcovid.com ↗	63 match 1 shared topics	Facts Not Fear - Understanding the COVID-19 Vaccine	en	infectious-diseases WordPress WooCommerce	robotsllmsaihumans	emailphone	none
elizabethtayloraidsfoundation.org ↗	63 match 1 shared topics	Home - The Elizabeth Taylor AIDS Foundation	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
etaf.org ↗	63 match 1 shared topics	Home - The Elizabeth Taylor AIDS Foundation	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
viroliegy.com ↗	63 match 1 shared topics	ViroLIEgy – Exposing the lies of Germ Theory and virology using their own sources.	en	infectious-diseases WordPress WooCommerce	robotsllmsaihumans	emailphone	none
mediaepidemics.com ↗	63 match 1 shared topics	Media and Epidemics (MEDEP) – Technologies of Science Communication and Public Health in the 20th and 21st Centuries	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
donttakethiswrong.com ↗	63 match 1 shared topics	Don't Take This The Wrong Way… – Antimicrobial resistance is an issue today.	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
donttakethiswrong.org ↗	63 match 1 shared topics	Don't Take This The Wrong Way… – Antimicrobial resistance is an issue today.	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none
viraltrails.com ↗	63 match 1 shared topics	Viral Trails: Crowd Sourced Tracking of Infected Pathways	en	infectious-diseases	robotsllmsaihumans	emailphone	none
vitassay.com ↗	63 match 1 shared topics	Vitassay Healthcare \| Identifying Pathogens Worldwide	en	infectious-diseases WordPress WooCommerce	robotsllmsaihumans	emailphone	none
helm-project.com ↗	63 match 1 shared topics	HELM Project – Eliminating STH & OV in the Lower Mekong Basin	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	full · 12
onehealthnevada.com ↗	63 match 1 shared topics	One Health Nevada \| Office of State Epidemiology	en	infectious-diseases WordPress	robotsllmsaihumans	emailphone	none

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:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

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.