Table 2.

Performance of different model quality assessment methods. “under” denotes the Undertaker cost functions; “under+TM,” the Undertaker cost functions with the median TM-score consensus term; and Qiu, data from a scoring function including the median TM-score consensus term, an atom-pairwise distance potential, and Rosetta terms [2]. TASSER, LEE, Pcons, and ModFOLD indicate CASP7 groups 125, 556, 634, and 704. The correlation measures are against negative GDT_TS (a,b) or real cost (c) and are averaged over 91 CASP7 targets. The metrics are Pearson's r, Spearman's ρ, average quality of predicted best model (GDT denotes GDT_TS; RC, real cost), Kendall's τ, and τ₃. Evaluation and training was done using five-fold cross-validation on all models and GDT_TS (a), complete models and GDT_TS (b); and complete models and real cost (c). Tables are sorted by the average quality of the best model. The largest value in each column is presented in bold; the second largest, italics.

1.1 (a)
Group	r̄	ρ ¯	GDT	τ ¯ 0	τ ¯ 3
under+TM	0.90	0.85	61.2	0.70	0.68
under	0.76	0.76	60.5	0.59	0.60
TASSER	0.64	0.70	60.3	0.55	0.53
Qiu	0.85	0.75	60.2	0.59	0.55
Pcons	0.82	0.75	58.6	0.56	0.52
LEE	0.82	0.78	58.1	0.64	0.59
ModFOLD	0.66	0.55	55.9	0.40	0.37
1.2 (b)
Group	r̄	ρ ¯	GDT	τ ¯ 0	τ ¯ 3
under+TM	0.90	0.84	61.8	0.69	0.66
under	0.86	0.78	61.0	0.62	0.59
Qiu	0.85	0.74	60.5	0.58	0.55
TASSER	0.63	0.69	60.4	0.54	0.52
LEE	0.80	0.72	58.4	0.58	0.53
Pcons	0.85	0.74	58.0	0.56	0.51
ModFOLD	0.70	0.62	57.0	0.46	0.44
1.3 (c)
Group	r̄	ρ ¯	RC	τ ¯ 0	τ ¯ 3
under+TM	0.93	0.88	47.5	0.73	0.70
under	0.91	0.84	38.5	0.68	0.66
Qiu	0.86	0.76	34.1	0.60	0.58
TASSER	0.70	0.74	30.7	0.58	0.56
LEE	0.80	0.72	14.5	0.57	0.52
Pcons	0.84	0.75	5.7	0.56	0.51
ModFOLD	0.76	0.69	14.9	0.52	0.50