A behavioral study showed that perceived eye gaze modulates performance in face recognition both at the encoding and retrieval levels, with better performance when facing someone with direct gaze, both in adults and children [46].
The method applied in this work allowed us to assess the extent and characteristics of the dominant water of the flood plumes, without depending on the retrieval of Level 2 MODIS data in Case 2 waters.
eFIP performance was evaluated for document retrieval, sentence-level information extraction and document ranking.
Despite comprehensive approaches to data identification and retrieval, individual-level intake data were limited for certain foods, countries and time periods; in particular, more intake data were available in 2010 than in 1990, and relatively few intake data were available in most Sub-Saharan African nations, and on nuts/seeds and whole grains.
These inform descriptions of the elevation retrievals of the level 2 processing, including the SARInM retrieval of interferometric phase.
The water level retrieval is done using Ice-1 retracking algorithm.
For the retrieval at leaf level, the estimation accuracy can be as good as RMSE = 0.0019 g/cm2 and R2 = 0.939 or better.
Document-oriented architectures, such as the commonly employed IHE XDS profile, which only support information retrieval at the level of documents, are particularly susceptible for this problem.
For the retrieval at canopy level, the model accuracy is RMSE = 0.0061 g/cm2 and R2 = 0.966 or better when PROSPECT-SAILH simulated reflectance was used; when AVIRIS image spectra were used, the model accuracy is RMSE = 0.0094 g/cm2 and R2 = 0.8734 for the calibration, and RMSE = 0.0132 g/cm2 and R2 = 0.7756 for the validation.
However, since false memories can only be measured with tasks requiring some form of retrieval on behavioral level, it is difficult conclude that the production of false memories at retrieval are not due to encoding or consolidation processes (see above).
