Maths has proofs. Logical reasoning from first arguments that a thing is true or not. It either is, or is not, proven. End of.

Physics as applied maths, pretty solid. We need to conduct experiments to verify that nature agrees with our mathematical constructs, but on the whole these are simple and unequivocal. e.g . gravity. Particle physics gets dodgy because of the vast range of collision results - statistics starts creeping in. Rather than being able to say that particle A collides with particle B to produce particles D an E, we now have a statistical chance that somethng might happen.

Chemistry as applied physics, again, pretty solid. Everything has to be tested by experiment, and experiment frequently throws up surprises, but if a reacts with B in Chicago, it probably does in Moscow too.

Biology as applied chemistry. Mostly solid. It gets massively complex, and so the temptation to resort to statistics is overwhelming and most biological papers start talking about statistical probabilities rather than actual results. But the basic biology is mostly the same for most subjects, and if the conclusion is simple (virology and the effectiveness of vaccines, for example) then we're all good.

Any social science as applied biology: not much. This is really dodgy territory where the experiment design totally dominates the result, and the result is statistical data that has to be massaged into a definitive statement. This is p-hacking territory, where experiments are largely unreproducible, very subject to bias, cultural references, and academia politics. E.g. whether creativity shares a limited resource pool with willpower - highly subjective, highly variable between individuals, hihgly suspect if your paper cites this as a proven result.

Not all science is worthy of the same level of trust. The scientific method is trustworthy. Academia is not.

Arguing with this is like disputing the fact that high heels make for terrible running shoes. Research in question with be quite similar.