Not exact matches
The immediate
comparison of real and
modeled neurons within the coding space allows both the
systematic investigation of the
model and the tuning of particular
model variants as found in the real animal.
NeuroStemcell is focused on the identification and
systematic comparison of progenitor cell lines with the most favourable characteristics for mesDA and striatal GABAergic neuronal differentiation, generated either directly from human embryonic stem (ES) cells, from Neural Stem (NS) cells derived from ES cells or fetal brain, from induced Pluripotent Stem (iPS) cells or from in vitro short - term expanded neural progenitors from ventral midbrain grown as neurospheres (VMN, Ventral Midbrain Neurospheres) 4, and perform rigorous and
systematic testing of the most prominent candidate cells in appropriate animals
models.
A
comparison of stellar densities from asteroseismology with densities derived from transit
models in Batalha et al. assuming circular orbits shows significant disagreement for more than half of the sample due to
systematics in the
modeled impact parameters, or due to planet candidates which may be in eccentric orbits.
The new 17 - author paper (accessible pdf)(lead by Ben Santer), does a much better job of comparing the various trends in atmospheric datasets with the
models and is very careful to take account of
systematic uncertainties in all aspects of that
comparison (unlike Douglass et al).
This was established on the
systematic comparison between
models» predictions with actual observations obtained over almost one solar cycle (1998 — 2007) at four European ionospheric locations (Athens, Chilton, Juliusruh, and Rome) and on the
comparison of the
models» performance against two standard prediction strategies, the median - and the persistence - based predictions.
In Phase II of AeroCom, a large - scale
model intercomparison was performed to document the current state of OA
modeling in the global troposphere, evaluate the OA simulations by
comparison with observations, identify weaknesses that still exist in
models, explain the agreements and disagreements between
models and observations, and attempt to identify and analyze potential
systematic biases in the
models.
Second, we could take the actual climate record from some «epoch starting point» — one that does not matter in the long run, and we'll have to continue the
comparison for the long run because in any short run from any starting point noise of a variety of sorts will obscure
systematic errors — and we can just compare reality to the
models.