Retaining rows that have percent overlapping ranges in Pandas

I have a dataframe with the columns: [id, range_start, range_stop, score]. If two rows have a range overlap by x percentage I retain the row with the higher score. However, I am confused how to pull out rows with no overlap to other ranges. I am using a nested loop and recursion to condense overlapping ranges into a new dataframe. However, this structure causes all rows to be retained when I am looking for the non overlapping rows.

## This is my function to recursively select the highest scoring overlapping regions

def overlap_retention(df_overlap, threshold, df_nonoverlap=None):
     if df_nonoverlap != None:
          df_nonoverlap = pd.DataFrame()
     
     df_overlap = pd.DataFrame() 
    
     for index, row in x.iterrows():
          rs = row['range_start']
          re = row['range_end']

          ## Silly nested loop to compare ranges between all rows 
          for index2, row2 in x.drop(index).iterrows():   
               rs2 = row2['range_start']
               re2 = row2['range_end']
               readRegion=[*range(rs,re,1)]
               refRegion=[*range(rs2,re2,1)]
               regionUnion = set(readRegion).intersection(set(refRegion))
               overlap_length = len(regionUnion)
            
               overlap_min = min(rs, rs2)
               overlap_max = max(re, re2)
               overlap_full_range = overlap_max-overlap_min

               overlap_percentage = (overlap_length/overlap_full_range)*100

               ## Check if they overlap by x_percentage and retain the higher score
               if overlap_percentage>x_percentage:
                    evalue = row['score']
                    evalue_2 = row2['score']
            
                    if evalue_2 > evalue:
                          df_overlap = df_overlap.append(row2)
                    else:
                         df_overlap = df_overlap.append(row)
#----------------------------------------------------------
                ## How to find non-overlapping rows without pulling everything?
               else:
                    df_nonoverlap = df_nonoverlap.append(row)
# ---------------------------------------------

          ### Recursion here to condense overlapped list further
          if len(df_overlap)>1:
              overlap_retention(df_overlap, threshold, df_nonoverlap)
          else:
              return(df_nonoverlap)

An example input is below:

data = {'id':['id1', 'id2', 'id3', 'id4', 'id5'],
       'range_start':[1,12,11,6,20],
       'range_end':[4,15,15,6,23],
       'score':[3,1,8,2,5]}
input = pd.DataFrame(data, columns=['id', 'range_start', 'range_end', 'score'])

The desired output can change based on the overlap threshold. In the example above id1 and id4 may both be retained or simply id1 depending on the overlap threshold:

data = {'id':['id1', 'id3', 'id5'],
       'range_start':[1,11,20],
       'range_end':[4,15,23],
       'score':[3,8,5]}
output = pd.DataFrame(data, columns=['id', 'range_start', 'range_end', 'score'])

from Retaining rows that have percent overlapping ranges in Pandas