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Mercato: 24h Vol: Cryptocurrencies: 2698 Bitcoin Bitcoin Condividere: 58.68%
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MarcoPolo Protocol Rango 2403
$0.041276
MarcoPolo Protocol Rango 2403
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0 MAP

MarcoPolo Protocol
MarcoPolo Protocol
MAP

MarcoPolo Protocol Prezzo
$ 0.0413

MarcoPolo Protocol 24h Vol
$4,353

MarcoPolo Protocol Mercato
$0

24h Vol
0 BTC
1 H
-0.23 %
24 H
-0.7 %
7 d
-14.65 %
Oggi MarcoPolo Protocol il prezzo in dollari USA è attualmente 0.0413 USD, e se convertito a Bitcoin è 0.00000446 BTC. Un totale di N/A sono attualmente in circolazione nel mercato. MarcoPolo Protocol i prezzi stanno attualmente subendo un cambiamento -0.7 %, dai un'occhiata tutta criptovaluta. Nelle ultime 24 ore 0.000 M US dollars MarcoPolo Protocol è stato scambiato su Scambi crittografici. Ottenere MarcoPolo Protocol's progredire aggiungendolo al tuo preferite e creando un libero portafoglio.
Nome e cognome
MarcoPolo Protocol
Simbolo
MAP
Algoritmo
BTC Prezzo
0.00000446 BTC
BTC Mercato
0 BTC
BTC 24h Vol
0 BTC
Monete totali estratte
0 MAP
1h
-0.23 %
24h
-0.7 %
7d
-14.65 %
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Descrizione

Descrizione


Maester is a term borrowed from the popular fantasy television series - The Game of Thrones, where Maesters, are an order of scholars, healers, and learned men in the Seven Kingdoms. Due to their scientific and intellectual pursuits, they are sometimes referred to as "the knights of the mind". In the context of the platform, a Maester means a professional that other users can reach out to for consultation. We believe every one of us has a skill or knowledge that others can imbibe from us and hence we call our users ‘Maesters’ and the digital currency associated Maester Coin. Hence our mantra, Anyone can be a Maester and earn more with Maester Protocol. 

Users can post blogs, pictures, and videos on the platform showcasing their skills or knowledge about the subject to establish thought leadership. This is called Professional Reputation Management or PRM. The Maester protocol through its proprietary algorithm generates a PRM score for every user by analyzing user demographic & activity variables using typical data mining technique of logistic regression.