Is there a method bias when I prefer a specific post-hoc that shows a significance after significance in test of difference in groups?

Question

I'm working to see if a machine does better than a worker in terms measurement (by having a measurement from an expert be the control). So my dataframe contains the Measurement Value, Measuring Device, and the slide number for the repeated measure. The Measurement wasn't normal so I used friedman test. The p.value was smaller than 0.05 so I proceeded to do post-hoc. Then I noticed most of the post-hoc tests showed no significance except one (Conover test).

1. How likely is a post-hoc to show no significance?
2. Is it wrong to just choose to report the post-hoc that showed significance?

rm(list=ls())

library(tidyverse)
library(PMCMRplus)

df1=structure(list(Measurement = c(1, 0, 0, 0, 0, 0, 0, 
0, 1, 0, 0, 3, 1, 1, 0, 1, 0, 1, 1, 2, 0, 0, 0, 2, 0, 0, 0, 1, 
0, 0, 0, 1, 0, 0, 0, 0, 0, 2, 0, 2, 0, 1, 1, 2, 0, 0, 2, 2, 2, 
0, 2, 1, 1, 0, 2, 0, 0, 0, 1, 1, 1, 0, 2, 0, 0, 0, 0, 1, 1, 0, 
0, 0, 3, 0, 2, 0, 1, 0, 2, 0, 0, 2, 2, 2, 0, 3, 1, 2, 0, 3, 0, 
0, 0, 0, 1, 1, 0, 3, 0, 0, 0, 0, 1, 0, 0), Device = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("Machine", "Expert", 
"Worker"), class = "factor"), `slide#` = c("1", "2", "3", "4", 
"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", 
"16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26", 
"27", "28", "29", "30", "31", "32", "33", "34", "35", "1", "2", 
"3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", 
"15", "16", "17", "18", "19", "20", "21", "22", "23", "24", "25", 
"26", "27", "28", "29", "30", "31", "32", "33", "34", "35", "1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35"
)), row.names = c(NA, -105L), class = c("tbl_df", "tbl", "data.frame"
))

attach(df1)


friedmanTest(Measurement,Device,`slide#`)

#has significant pair
frdAllPairsConoverTest(Measurement,Device,`slide#`)

#has no significant pair
frdAllPairsExactTest(Measurement,Device,`slide#`)
frdAllPairsMillerTest(Measurement,Device,`slide#`)
frdAllPairsNemenyiTest(Measurement,Device,`slide#`)
frdAllPairsSiegelTest(Measurement,Device,`slide#`)