With pens and corrals, the animals can be moved naturally from one point to another, following the one ahead of them. There are specific ways to design facilities to move animals through slaughterhouses naturally.
In some places they're still being used though.
Temple Grandin is the woman who got her PhD related to animal husbandry despite having autism then designed the humane method of leading cows to slaughter …her method is required in California but not all states are required to use it. Google the movie “Temple Grandin” it’s a cool movie
Your product is cool. Now what? How would you monetize it, or sell it?
If you did, what's the competition like? Can you carve out a niche for yourself?
...Now that you're properly discouraged - can you overcome all those challenges? If you can, calculate how much effort(look: money) it would take to do make your product into a money-making product; something you can sell...
...And then decide whether it might just be worth trying, even if the chances are small, even if you need to buckle up and work like a horse.
The tests are much more likely to successfully diagnose you if you take them near your peak viral load. Multiple tests over several days gives you more chances to sample near that peak.
If it were just that then taking the tests three times at once would have a similar effect. Instead, it's mostly that you're measuring a quantity that's varying over time, and more samples gives you more chances for one of them to be at a time when the quantity is high.
The math is more intuitive if you say it decreases the failure rate. i.e. if you try something with a 10% success rate 3 times, your odds are 1 - (0.9 ^ 3) = 27.1% chance of success.
The problem is also that intelligence isn't on some kind of a line where a specific test tells you that you're closer to a base amount of intelligence needed for sentience. It's a whole bunch of things combined in some yet to be defined way that ends up allowing for the development of intelligence.
As for GPT-4 - it can't even recognize for itself whether data is good or bad, and it can't even recognize that it doesn't know something; IMO right now it's still basically just a black box that takes an input and produces a statistically matching output. A very good one, but still.