Confidence is calculated as Pa-Pi value.
Pa (probability "to be active") estimates the chance that the studied amino acid sequence of CDR3 TCR is belonging to the sub-class of amino acid sequences of CDR3 TCR interacted with the appropriate epitope or MHC type (resembles the structures of molecules, which are the most typical in a sub-set of "actives" in PASS training set). We may considered interaction between amino acid sequence of CDR3 TCR and epitope or MHC type as activity of amino acid sequence of CDR3 TCR.
Pi (probability "to be inactive") estimates the chance that the studied amino acid sequences of CDR3 TCR is belonging to the sub-class of amino acid sequences of CDR3 TCR which don not interact with the appropriate epitope or MHC type (resembles the structures of molecules, which are the most typical in a sub-set of "inactives" in PASS training set)..
IAP (Invariant Accuracy of Prediction) is the average accuracy of prediction that is obtained for the whole PASS training set in leave-one-out cross-validation procedure.
IAP equals numerically to ROC AUC
Leave-one-out cross-validation (LOO CV) procedure is performed using the whole PASS training set for validation of prediction quality. The prediction result is compared with known experimental data for the studied amino acid sequence of CDR3 TCR. The procedure is repeated for all amino acid sequence of CDR3 TCR from the PASS training set; then the average Invariant Accuracy of Prediction (IAP=1-IEP) values are calculated for each biological activity and for all biological activities.
Only activities with Pa > Pi are considered as possible for a particular amino acid sequence of CDR3 TCR (Confidence >0).
It is necessary to remember that probability Pa first of all reflects the similarity of molecule under prediction with the structures of molecules, which are the most typical in a sub-set of "actives" in the training set. Therefore, usually there is no direct correlation between the Pa values and quantitative characteristics of activities.
Even active and potent amino acid sequences of CDR3 TCR, whose sequences is not typical to the sequences of "actives" from the training set, may obtain a low Pa value and even Pa < Pi during the prediction. This is clear from the way how the functions Pa(B) and Pi(B) are constructed: the values Pa for "actives" and Pi for "inactives" are distributed fully uniformly. Taking this into account, the following interpretation of prediction results is possible.
If, for instance, Pa value equals to 0.9, then for 90% of "actives" from the training set the B values are less than for this compound, and only for 10% of "actives" this value is higher. If we decline the suggestion that this compound is active, we will make a wrong decision with probability 0.9.
In case if Pa value is less than 0.5, but Pa > Pi, then for more than half of "actives" from the training set the B values are higher than for this compound. If we decline the suggestion that this compound is active, we will make a wrong decision with probability less than 0.5. In such case the probability to confirm this kind of activity in the experiment is small, but it will be confirmed more than 50% chances that this structure has a high novelty.
If the predicted biological activity spectrum is wide, the structure of the compound is quite simple, and does not contain peculiarities, which are responsible for the selectivity of its biological action.
If it appears that the structure under prediction contains a few new MNA descriptors (in comparison with the descriptors from the compounds of the training set), then the structure has low similarity with any structure from the training set, and the results of prediction should be considered as very rough estimates.
Based on these criteria, one may choose which activities have to be tested for the studied compounds on the basis of compromise between the novelty of pharmacological action and the risk to obtain the negative result in experimental testing. Certainly, one will also take into account a particular interest to some kinds of activity, experimental facilities, etc.