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SVD_ytt_3.blue
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SVD_ytt_3.blue
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[general]
observables = 1
measurements = el mu
uncertainties = stat EffectiveNP-MODEL1 EffectiveNP-STAT1 EtaIntercalibration-Theory btagsf closeby flavor-response ifsr jes lepidsf leprecosf lumi mcatnlo mu_qcd_shape muid mums musc pdf ps qcdE el_qcd_shape qcdM wjets_bbccc wjets_ca
[measurements]
el = 67.919
mu = 70.4596
[uncertainties]
el_u = 1.37551 1.44521 0.83577 0.228172 3.53811 0.932167 0.8377 2.24592 1.1588 1.71899 0.76059 1.22254 7.21892 0. 0. 0. 0. 0.0278168 1.15855 1.0188 0.0840015 0. 1.11067 0.820602
el_d = 1.37551 1.51167 0.903961 0.414192 2.97337 1.09524 0.793198 2.24592 1.24858 1.63954 0.738777 1.22254 7.21892 0. 0. 0. 0. 0.030899 1.15855 0.995903 0. 0. 1.064 0.954247
mu_u = 1.317 1.3724 0.811615 0.28949 3.69176 0.629486 0.689079 1.56044 0.981049 0.596085 0.257965 1.26827 6.36252 0.0126648 0.0537415 0.0124512 0.057724 0.0329285 2.09669 0. 0. 0.224838 0.990952 0.843735
mu_d = 1.317 1.55986 0.939423 0.276321 3.12458 0.730865 0.737877 1.56044 0.889107 0.582428 0.251396 1.26827 6.36252 0.0170746 0. 0.00737762 0.057724 0.0362396 2.09669 0. 0. 0.223839 1.09389 0.95742
[correlations]
stat = [ [ 1, 0 ], [ 0, 1 ] ]
EffectiveNP-MODEL1 = [ [ 1, 1 ], [ 1, 1 ] ]
EffectiveNP-STAT1 = [ [ 1, 1 ], [ 1, 1 ] ]
EtaIntercalibration-Theory = [ [ 1, 1 ], [ 1, 1 ] ]
btagsf = [ [ 1, 1 ], [ 1, 1 ] ]
closeby = [ [ 1, 1 ], [ 1, 1 ] ]
flavor-response = [ [ 1, 1 ], [ 1, 1 ] ]
ifsr = [ [ 1, 1 ], [ 1, 1 ] ]
jes = [ [ 1, 1 ], [ 1, 1 ] ]
lepidsf = [ [ 1, 1 ], [ 1, 1 ] ]
leprecosf = [ [ 1, 1 ], [ 1, 1 ] ]
lumi = [ [ 1, 1 ], [ 1, 1 ] ]
mcatnlo = [ [ 1, 1 ], [ 1, 1 ] ]
mu_qcd_shape = [ [ 0, 0 ], [ 0, 1 ] ]
muid = [ [ 0, 0 ], [ 0, 1 ] ]
mums = [ [ 0, 0 ], [ 0, 1 ] ]
musc = [ [ 0, 0 ], [ 0, 1 ] ]
pdf = [ [ 1, 1 ], [ 1, 1 ] ]
ps = [ [ 1, 1 ], [ 1, 1 ] ]
qcdE = [ [ 1, 0 ], [ 0, 0 ] ]
el_qcd_shape = [ [ 1, 0 ], [ 0, 0 ] ]
qcdM = [ [ 0, 0 ], [ 0, 1 ] ]
wjets_bbccc = [ [ 1, 1 ], [ 1, 1 ] ]
wjets_ca = [ [ 1, 1 ], [ 1, 1 ] ]