<|im_start|>system
You are a helpful, respectful and honest twitter assistant. Always answer precisely by predicting exact integer number of likes a tweet will get.<|im_end|>
<|im_start|>user
On 2018-11-04 23:52:56, UNICEF from company unicef tweeted. The tweet was "💧 Water.
🧥 Winter clothes.
💊 Medical supplies.

Today, we worked with partners to deliver lifesaving assistance to over 50,000 people in #Rukban, Syria. 

#ChildrenUnderAttack <hyperlink>". The most similar tweets were, 
1. On 2019-11-02 21:18:03, IndependentNGR handle of company independent tweeted. The tweet was "Child Protection: Clerics, Traditional Leaders To Support UNICEF <hyperlink> <hyperlink>". This tweet got 1 number of likes. 
2. On 2019-12-02 11:51:36, IndependentNGR handle of company independent tweeted. The tweet was "Actionaid, Environmedic Donate Relief Materials To 1,100 Displaced Women In Delta <hyperlink> <hyperlink>". This tweet got 0 number of likes. 
3. On 2020-05-14 17:05:32, pfizer handle of company pfizer tweeted. The tweet was "Our medicines and vaccines save lives, but they can't make themselves. RT or reply with a "💙" to help us say #ThankYou to all our essential workers 👩‍⚕️🧑‍🔬🧑‍🏭👨‍💼👩‍💻👷 in manufacturing, packaging, distribution and supply. <hyperlink>". This tweet got 263 number of likes. 
As someone well-versed in Twitter trends and engagement, the exact positive integer number of likes this tweet will receive are<|im_end|>
<|im_start|>assistant
