First of all, the important thing is the R number - how many people does the average infected person infect. If that is above 1, you get spread. Below 1, it dies out. Without mitigations, R is estimated at about 3. With mitigations, the UK is posting various numbers in the 0.7-1.0 range. (See https://www.bbc.com/news/health-52473523 for a source.) Let's assume that the USA is similar.
The question to ask is this. Do the temperature checks make the difference between being above or below 1.0?
Per https://www.webmd.com/lung/news/20210110/59-percent-of-covid... about 60% of spread comes from people who are asymptomatic. So about 40% happens from people who are symptomatic. Per https://www.healthline.com/health-news/what-is-the-risk-of-g... about 55% of spread happens at stores. If those factors were independent, about 1/4 of the spread would happen from symptomatic people at stores. If the temperature checks avoid a significant fraction of those, then in the real world it may indeed be the difference between pandemic spread and dying off.
obviously 37 practically isn't a fever, and 32 is ridiculous.
But let's accept it on face value, so it gave you a false positive, which caused you to pause for a second reading, and then a true negative (well, unless you count the 32 as a false positive for hypothermia) and you went in.
That temp checks create false readings isn't really news: for me the question is so they create statistically significantly better outcomes. As a statistics guy, my head says they do. The objections I hear to them sound to me like the objections to bmi: that it's not universally perfect is not reason to dismiss it. This seems to me like the perfect being the enemy of the good enough.