Sentence examples for mean precision for from inspiring English sources

To evaluate serial order effects, we calculated mean precision for each of the three serial positions (SP) of the three-item VWM task, i.e. first (SP1), second (SP2) and third item in sequence (SP3).

Results of retrieved citations are adjusted based on these factors but they are not the real subjects of the citations (mean precision for fully relevant citations: 21.1%, 23% respectively).

Furthermore, the mean precision for MetaPSICOV of 0.54 indicates that correct predicted contacts are more likely than incorrect contacts, which is an important performance threshold in terms of accurate 3D model building from predicted contacts (Hopf et al., 2012; Kosciolek and Jones, 2014; Marks et al., 2011; Michel et al., 2014; Nugent and Jones, 2012).

The mean precision for fully relevant citation was 48.4%CI95%% = [45.8-50.9] buthisis number does not reflect discrepancies between evaluators: three evaluators (BT, GK and NG) found full relevance around 40% (43.7%, 36.7% and 37.4%, respectively) and one (LR) found 75%.

The table shows the mean precision for each algorithm, the lower and upper 95% confidence limits for the difference in precision (DP-GR) and the associated t-test p-values Comparison of the DP, GR, and SR spatial recall obtained from model selection.

Table 10 Mean average precision for multiple sources of evidence Multiple sources of evidence MAP Description + metatags 19.37 Description + passage 24.69 Metatags + passage 29.27 Description + metatags + passage 27.40.

They obtained the highest mean average precision for maximum flow approach which indicates the method has a better performance than the stated approaches.

Table 9 Mean average precision for sources of evidence in isolation Sources of evidence MAP Meta tags 18.17 Description tags 9.13 Text passage 26.79.

The mean average precision for the novel MEDLINE relationships (02/2007 to 04/2010) and the novel CTD relationships (11/2008 to 04/2010).

Results: Using the original PSICOV benchmark set of 150 protein families, MetaPSICOV achieves a mean precision of 0.54 for top- L predicted long range contacts around 60% higher than PSICOV, and around 40% better than CCMpred.

She calculated a mean precision of about 3% for systematic reviews with a large range [ 51].