Comparisons of models with data are, for example, referred to
as model validation studies rather than model tests.
Reactor enables evaluation of reactive materials for solar ‑ thermochemical hydrogen production under real ‑ world conditions, and provides a learning platform for up - scaling technology as well
as model validation.
Not exact matches
But it's also interesting
as validation of a
model that's becoming increasingly popular: Companies that are private only in name.
Cryptocurrency mining itself refers to a type of
validation model known
as «proof - of - work» (PoW).
A range of factors have driven this shift, including a sharp reduction in the cost to advance technology companies to proof of concept and business
model validation — aided by declining infrastructure expenses, the rise of cloud - based software and service providers, and «pay
as you grow» cost structures.
Teams organically form around the top ideas (
as determined by popular vote) and then it's a 54 hour frenzy of business
model creation, coding, designing, and market
validation.
The new technique could provide a much - needed experimental
validation of frequently used computational
models,
as well
as a means of investigating the effect of new battery materials and additives on lithium metal plating.
They also used tenfold cross
validation to train the
models for responsiveness, and then tested these on the
validation samples
as well.
The specific goal of releasing space - weather data from national - security assets such
as GPS satellites is to enable broad scientific community engagement in enhancing space - weather
model validation and improvements in space - weather forecasting and situational awareness.
I can read any peer - reviewed article I like on modern climate
models, but until I go through much of the process of building, running,
validation, discussing with colleagues how they solved particular wrinkles etc of some
models, I am unlikely to fully comprehend climate
modelling as a skilled craft.
Our goal in using this multifaceted
model was two-fold 1) to confirm and further characterize the distinct behavioral traits in animals most susceptible to social stress after going through the 10 - day social defeat paradigm compared to undefeated control animals; 2) to provide pharmacological
validation for this
model using standard antidepressant medications such
as fluoxetine and imipramine.
«This is the first biological
validation of a computational
model developed in the early 1980s that suggested that two such forces would be necessary to guide axons
as they establish the connections that relay spatial information from one part of the nervous system to another,» said study author Yimin Zou, PhD, assistant professor of neurobiology at the University of Chicago.
The ICS is a large - scale facility open to the community that ensures the generation of mouse
models à la carte, the
validation of genetic
models, the expansion and preservation and distribution of
models with the housing department, and offers in its phenotyping department a series of standardized functional analysis of mouse
models that can be performed in a comprehensive pipeline or on demand,
as well
as for more specialized studies, that cover the major functions and key physiological systems.
The phenotyping platforms of PHENOMIN - ICS area, adapted to study genetically modified mouse
models, can also be used for preclinical studies, including the
validation of therapeutic targets,
as well
as pharmaceutical and toxicological studies in mice.
The role of new genetic pathways in cancer biochemistry (the genome mutation profiles), the identification of the key targets and their
validation,
as well
as utilization of new knock - out or knock - in animal
models for such studies are among topics that will be discussed.
I proposed an invited session for the 2016 ASHG meeting because I believe that inherited retinal diseases offer several key advantages
as a
model system for gene discovery, functional
validation, genetic counseling, and individualized treatment.
Modeling Kepler transit light curves
as false positives: Rejection of blend scenarios for Kepler - 9, and
validation of Kepler - 9d, a super-Earth-size planet in a multiple system
As part of the SFI Investigators Programme 2016 call, SFI is providing applicants with the opportunity to seek funding to support the development and
validation of new tests,
models and approaches not involving the use of live animals and / or addressing the principles of the 3Rs (Replacement, Reduction and Refinement).
«We actually view it
as flattery, we see Overdrive's imitation of our lend - first
model as validation that it is a wise investment for libraries, and that it is the best way to end patron dissatisfaction and provide timely, topical and relevant titles to patrons.»
In an industry that many still perceive
as having a chip on its shoulder towards self - publishing and digital publishing, the atmosphere was very welcoming of those who choose to forgo the traditional
model, demonstrating the
validation and respect that indie publishing and its technology have earned in recent years.
«All information collected from the user is collected solely for purposes such
as license
validation and to facilitate the implementation of different licensing
models by publishers,» Adobe said in a statement.
Rail: You were sort of parallel to the Pictures Generation, this moment that required
validation for photography to be shown
as artwork, but also
as an acceptable reference for a painter,
as opposed to using a live
model.
I understand the argument that past projections are based on estimated future forcings which can change, but this amounts to the same things
as tuning hindcasts and declaring matching a hindcast to observations
as a
validation of your
model.
As to validated, I was speaking in terms of
model validation — verification of trends in the
model against data, etc..
I can read any peer - reviewed article I like on modern climate
models, but until I go through much of the process of building, running,
validation, discussing with colleagues how they solved particular wrinkles etc of some
models, I am unlikely to fully comprehend climate
modelling as a skilled craft.
Dynamical
models include the physics
as best it can be determined — so their agreement with observations is their
validation.
We have been treated to many opportunistic hindsight «
validations» of climate
modeling (Pakistan, Russia, etc.) using the «consistent with» meme that most scientists would see
as very weak evidence.
The fact that the RCM - based downscaling approach can reproduce the observed changes when fed modern reanalysis data is used by Knutson et al
as a «
validation» of the
modeling approach (in a very rough sense of the word — there is in fact a non-trivial 40 % discrepancy in the
modeled and observed trends in TC frequency).
MM2005 did not «
model a stationary process», they
modelled a non-stationary process
as a stationary ARFIMA process and unusually did not attempt any
validation statistics for their
model.
Verification &
Validation of
models is a standard process in NASA
as in most fields of science... Except obviously in climate science!
More accurate and reliable precipitation data would be invaluable, not only for the study of climate trends and variability, but also
as inputs to hydrological and ecological
models and for
model validation, characterization of extreme events, and flood and drought forecasting.
However, it would then be more appropriate to measure the ability of the
model to fit the proxies in the
validation period rather than its ability to back out temperature,
as they apparently have done.
The resulting best - estimate temperature data product for Lauder is expected to be valuable for satellite and
model validation as measurements of atmospheric essential climate variables are sparse in the Southern Hemisphere.
The number of events that are available for
validation is 15 less the number used in
model building tasks such
as assignment of numerical values to parameters.
An early draft of Climate Change 95 had a Chapter titled «Climate
Models —
Validation»
as a response to my comment that no
model has ever been validated.
The spatially and temporally averaged global surface temperature defines a set of outcomes that is unsuitable for the
validation of a
model as the number of outcomes in the set of all outcomes is unbounded.
I agree an observation /
model mix is required (e.g. such
as with the reanalyses), but the absence of observational
validation is what is a fundamental flaw in the use of Type 4 downscaling for multi-decadal impact assessments,
as I have explained in detail in my posts.
Under a logical approach to
validation, each prediction that is made by a predictive
model is viewed
as making a claim about the outcome of a statistical event and this claim is viewed
as a logical proposition.
As climate
models become increasingly relevant to policy makers, they are being criticized for not undergoing a formal verification and
validation (V&V) process analogous to that used in engineering and regulatory applications.
Brandon, the answer is already in my original comment: 1) None of the climate
models has been subjected to a formal V&V process (no
validation report available) 2) None of the
models is able to formally hind - cast past observations and
as a matter of fact there is a significant mismatch between
models outputs and measurements over [1880 — 1970] and [2000 — 2010] periods, which means that all
models would have failed to pass such a
validation process.
The proper way is set aside the most recent data
as validation data, and «train» the
model only on prior data.
So, we'll probably have to wait 30 some years for our
validation (
as will those climate
models!).
Calypso allow visualisation and interactive analysis to various data used or produced by GlobWave project for the
validation or inter-comparison with satellite data, such
as buoys, satellite / buoy matchups or
model outputs.
Therefore, this study casts considerable doubt on all current global warming
models, which rely on this data
as validation.»
Excellent post with several significant points, but still a focus on tropospheric temperatures
as «
validation» for the
models is a very weak argument.
For example, all estimates of government revenue and outgo depend on some sort of economic
model, which superficially have the same weaknesses
as climate
models:
validation issues, adjustable parameters, some key processes (convection, precipitation, human behavior) can't be reliably
modeled.
To test the theory that seasonal forecasts SSTs would perform
as well
as observed SSTs and result in very similar attribution statements, scientists from the CPDN team compared weather@home in forecast mode (forced with seasonal forecast SSTs) relative to hindcast mode (forced with observed SSTs)
as part of a
model validation effort.
On my side, I consider that science
as a whole is a
model, there is no fundamental difference between numerical
models and physical laws, except the degree of
validation and thus trust.
Cross
validation is way of looking at data that does not have out - of - sample data for
model testing and that would include such comprehensive methods
as k-fold cross-
validation.
So it then occurred to me that if you are comparing the output from a climate
model with actual measures at a grid level there was a risk that both datasets would suffer from spatial autocorrelation, and this should be tested for before using standard statistics
as validation of the
model output.