applying after bachelor's degree which factor is the most important for top 10 I am a student willing to apply for top 10 universities(MIT, Stanford, etc).
I have recently graduated with a bachelor's degree in Computer Engineering field with GPA 4.5/5. 

I have read about important factors for applying and I found out that these factors are the most important factors ( from most important to least important)


GPA
Recommendation Letters
GRE Scores
Research/Getting Papers Published
Industry Internships
Being a TA


(Main Question) I want to how much GPA is important for example a person with GPA 4.8 is far more likely to be accepted than me or not. for example, students with GPA above 4.5 are all the same. 

and my second doubt is about the rank of papers. If you publish a paper in famous journals is it that much unimportant to them?

what about doing something extraordinary. I am developing an AI program that is really professional and I am writing a paper related to this program. I want to know how much these sorts of activities are important for them.
I think it's useful for this question to step back and think about it from first principles.

What a top graduate program wants in a graduate student is high likelihood of becoming a leading researcher in the field.  There are some exceptions, but for most applicants at most leading departments, this is the only consideration.

The problem with putting this forward as a criterion is that no one can predict the future.  You really don't know whether you're going to become a leading researcher, and neither do the people reading your application.  Everyone is trying to make their best guess based on the information available.

At this point, someone is going to ask for a data-based solution, but the problem is that there really isn't that much data.  There aren't that many leading researchers, the factors that make leading researchers likely change quite a bit over time, so the kinds of people that did well twenty years ago might not do so well now, and the variables probably interact with each other in complicated, nonlinear ways that are hard to tease apart statistically without large amounts of data.

This means graduate admissions boils down to a committee of people reading applications and making their best judgement as to who is most likely to become a leading researcher.  You can now ask the psychological (or maybe sociological) question about what factors professors on admissions committees think correlate with probability of becoming a leading researcher, but there seems to be quite high variability between individuals, and you don't know who is sitting on admissions committees that year.

Given how difficult it is to determine how all these proxy measures work, I think it's best to believe that admissions committees will get it right and look at what they're really trying to measure - your probability of becoming a leading researcher - with the caveats that you should consider the judgement of other people you trust to have an informed opinion (your current professors) and that your own judgement is highly likely to be biased by imposter syndrome and or the Dunning-Kruger effect.