A SIMCA (soft independent modeling of class analogy) model was built using the scores from the PCs to a confidence level of 95%, which is completely specific (100%) for the vapors of each explosive and explosive mimic.
The score confidence limits used are given by where ^ p denotes the sample proportion, n denotes the sample size, and zα/2 denotes the 1 – α/2 quantile of the standard normal distribution (8 ); α was set to 0.05 to obtain 95% confidence limits.
The links are stored in EMPRES-i, and subsequently reviewed by FAO experts using the confidence scores as initial guidance.
Although PhymmBL can potentially make rank flexible selections using the confidence scores assigned to different rank levels, we were not able to implement an automated threshold that demonstrated good results.
Further adjustment of the exposure metrics using the exposure confidence score yielded virtually identical results and are not reported.
If an interaction edge is endorsed by both high confidence and low confidence experiments, we use the confidence score from the low-throughput column in Table 1 plus 5% times the number of high-throughput endorsements; however, if this value exceeds 95%, we still assign a maximum confidence score of 95%.
Confidence intervals (95%) for in-hospital mortality were computed using the Wilson score interval; confidence intervals for LOS and economic costs were computed using nonparametric bootstrapping (percentile method) from the study population (1,000 replicates with replacement).
However, there is no predefined high confidence data in MINT and IntAct, thus we used the confidence score to collect the high-throughput data from MINT and IntAct.
The readers were asked to assess the presence of residual tumor and/or metastasis based on a "subjective" visual assessment of the images using the following confidence level scores: 0, definitely no residual tumor/metastasis; 1, probably no residual tumor/metastasis; 2, unclear; 3, probably residual tumor/metastasis; 4, definitely residual tumor/metastasis.
Open IE uses the confidence score of each extraction as a threshold.
