<|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 2019-07-12 16:36:04, UPMCnews from company upmc tweeted. The tweet was "A new study is looking to artificial intelligence to address the opioid crisis by identify people who may be at risk for opioid overdose. Dr. Walid Gellad (<mention>) explains. <hyperlink> via <mention> <hyperlink>". The most similar tweets were, 
1. On 2018-03-11 18:44:45, cnnbrk handle of company cnn tweeted. The tweet was "Exclusive: Doctors who got more money from opioid makers were more likely to prescribe large amounts of opioids as the crisis ravaged the US <hyperlink> <hyperlink>". This tweet got 983 number of likes. 
2. On 2018-04-02 17:30:17, CNN handle of company cnn tweeted. The tweet was "Marijuana legalization could help offset the opioid epidemic, studies find <hyperlink> <hyperlink>". This tweet got 1509 number of likes. 
3. On 2018-04-07 12:01:05, CNN handle of company cnn tweeted. The tweet was "Marijuana legalization could help offset the opioid epidemic, studies find <hyperlink> <hyperlink>". This tweet got 1865 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
