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[quote=Anonymous][quote=Anonymous][quote=Anonymous][quote=Anonymous]Have been using gpt to estimate admission ratings, found it very helpful.  Basically plug in the stats and ECs, and ask gpt to evaluate each of the following:
Academic
Extracurricular
Athletic
Personal

Academic rating is based on rigor in the school context, gpa in the school context, test score, recommendation (if teachers told you what they are going to write).

EC rating is based on leadership, depth, impact, initiative, etc.

Athletic is the most definitive.  DC got a score of 3.  1 is for D1 recruit, 2 is for D3 recruit.  3 is for varsity / club level.

It's fun.[/quote]

To do this well or completely, you need to input the scoring rubric FOR each college along with the CDS (showing what the school values). Some of the scoring rubric for certain schools is in the link below. Its different for each school - as you can see even in the link some schools view ECs more importantly than other schools.

https://www.dcurbanmom.com/jforum/posts/list/1224166.page[/quote]

I did something similar, using that old, linked thread for my '25 graduate. It was pretty accurate, to be honest - kid is headed to a T10.

Used the paid version of Claude and turned off data sharing. You have to do each school separately and upload as much info as you can get your hands on for each college, one by one (save each as a new "Project" in Claude).
For each college, include all admissions info you can get your hands on. I included transcripts of interviews with AO from the school, material from the school's website, and any Reddit posts where someone reviewed their application in the past few years and viewed their file—also included info from our high school on # admitted each year.
Then, uploaded a draft pdf of the Common App for that school (so Claude had access to all info about the applicant - incl major, essays, ECs).
Next, ask for a very detailed review by the categories or scoring rubric for that particular college. Continue to "push" the AI bot to think harder and more critically, including identify the weakness in the application. 
Lastly, give it [b]Reddit r/collegeresults data too for that school in the last 2 years[/b] to see if it can add that data to its decision-making.
[/quote]

For DC, we were using school data not using outside data because the school gpa is deflated.  Calibration is done using only our school's past data, whatever that is available.  
You can instruct gpt to ignore outside data but it's not necessary.[/quote]

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