Sentences with phrase «predictive models which»

Not exact matches

The Upshot blog at the New York Times, which has a predictive model of its own, never gave Trump more than a 40 % chance of winning the election.

To assess the robustness of the results of our regression analysis, we performed covariate adjustment with derived propensity scores to calculate the absolute risk difference (details are provided in the Supplementary Appendix, available with the full text of this article at NEJM.org).14, 15 To calculate the adjusted absolute risk difference, we used predictive margins and G - computation (i.e., regression - model — based outcome prediction in both exposure settings: planned in - hospital and planned out - of - hospital birth).16, 17 Finally, we conducted post hoc analyses to assess associations between planned out - of - hospital birth and outcomes (cesarean delivery and a composite of perinatal morbidity and mortality), which were stratified according to parity, maternal age, maternal education, and risk level.

Let's first give a very brief sketch of some of the main preoccupations of post-war liberal economic theory, which sought to understand the actual behaviour of economic agents under conditions of scarcity through the creation of predictive models.

For an upset to occur there has to be abnormal voter turnout, which is a problem for predictive modeling.

Despite the plethora of research, more needs to be done, said the report, which ends with a wish list of critical research needs including better predictive capabilities and models, as well as ways to measure the socio - economic impacts of drought outside of money spent by the Forest Service suppressing fires.

Gerber co-directs UVA's Predictive Technology Laboratory, which uses data to create predictive models with the goal of promoting better decisiPredictive Technology Laboratory, which uses data to create predictive models with the goal of promoting better decisipredictive models with the goal of promoting better decision making.

The DNNs are based on predictive coding theory, which assumes that the internal models of the brain predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models.

Dr. Miller and colleagues are developing an app that uses the predictive model, the equations for which are published in the paper.

He says previous predictive models of Greenland's ice loss did not adequately take into account the faster movement of its southern glaciers, which is accelerating the amount of ice entering the ocean: «Greenland is probably going to contribute more to sea level rise, and faster than predicted by these models.»

This paleo climatic data and the distribution of archaeological sites associated with the HP, as well of that of the Still Bay tradition, which existed in the same environments about 5,000 years before (76,000 to 71,000 years ago), enabled the researchers to model the emergence of these traditions with two predictive algorithms that permitted them to reconstruct the ecological niche associated with each tradition and determine whether these niches differed significantly through time.

He has initiated collaborations with theorists to simulate the formation of prenucleation clusters and come up with a predictive model of which minerals his theory may apply to.

These «hyper - predictive» models could be used to quickly predict which new chemical compounds could be promising drug candidates.

Jiacan Yuan is a climatologist who is interested in understanding the fundamental dynamical processes in the atmosphere and improving climate models, which could give us better predictive power and risk assessment of the changing climate.

We now have the necessary tools to develop these predictive models and improve the treatment of PTSD, which offers great hope for patients.

Developing such predictive models can help us to identify who would benefit most from immediate care following trauma and which type of care would be best.

The research team identified predictive models of transcription — the first step in gene expression — when the yeast cell is responding to osmotic stress (salt), which greatly affects cell growth.

In the case of K = 10 (which is what we simulated), we can also look at which genes the predictive model is using for each cell type.

It goes by standardized test scores, and holds teachers accountable for what's called student growth, which comes down to the difference between how well students performed on a test and how well a predictive model «expected» them to do.

Automatic models equipped with navigation benefit from the Rolls - Royce Wraith - like Predictive Drivetrain which uses GPS data to pick out the right gear to suit what's ahead, reducing unnecessary shifting through corners, roundabouts or highway exits.

Mauboussin explores three variables that might be predictive of such persistent high ROIC: corporate growth, the industry in which a company competes, and the company's business model.

Shedding student debt is a whole new game when your rate is based on Upstart's predictive modeling algorithm, which measures your potential future income — not just what you're currently earning.

Since the 1950s, social scientists have been comparing the predictive abilities of traditional experts, and what are known as «statistical prediction rules,» which are just simple models.

To determine which combination of measures best predicted outcome, we tested the discrimination, or performance, of each model by calculating the area under the curve (AUC), which quantified each model's ability to classify a dog correctly as an eventual program release or success (higher AUCs indicate better predictive power)(54, 55)(SI Materials and Methods).

Focusing especially on anything in that which might enhance our solving the coming climate change catastrophe before it happens or enabling climate models to be enhanced in their predictive power.

Since our real system does have a sort of lid (which builds or releases excess of «pressure», flipping quasi-randomly), the statement that «average boiling temperature is 100C, and we perfectly know how it depends on pressure» does not have any predictive power since you deliberately excluded ways / models to predict what the actual pressure might be.

eg pg xii To improve our predictive capability, we need: • to understand better the various climate - related processes, particularly those associated with clouds, oceans and the carbon cycle • to improve the systematic observation of climate - related variables on a global basis, and further investigate changes which took place in the past • to develop improved models of the Earth's climate system • to increase support for national and international climate research activities, especially in developing countries • to facilitate international exchange of climate data

Instead, the tendency has been to just look at static mean geographic patterns of things, which has been shown over and over again not to have much predictive value, with a couple of exceptions (e.g. see a nice 2010 paper by Trenberth and Fasullo [summary here] that relates one chronic model mean cloud error to climate sensitivity).

Furthermore, methanesulfonic acid generated simultaneously in OSC oxidation will become a significant contributor to particle formation, which should be taken into account in predictive models of air pollution and climate and may be especially important in agricultural areas with significant OSC sources.

An important one is that we need predictive models for policy, which should remind Denizens of the linear model.

A variant on this contrarian meme is the one according to which unless models are predictive, they're worthless.

Willard: A variant on this contrarian meme is the one according to which unless models are predictive, they're worthless.

A stern lesson from history Wyatt / Curry stadium waves require confirmation from analysis and computation; otherwise they risk being regarded as one more statistics - driven model, of which the climate literature already contains innumerably many... this large corpus of cycle - seeking pure - statistics climate models is (rightly) ignored by most scientists, due to the dismal track record of cycle - seeking science in regard to explanatory and predictive power.

Heck, basing public policy on any model which does not show predictive accuracy makes no sense.

If you were to produce a chaotic model using the above, I would venture a prediction that the above former were the massive attractors about which we could make some decent predictions about the future but that the latter human produced CO2 inserted into our atmosphere would leave us with hopelessly inadequate and wrong predictions because CO2 contributed by man is not an attractor of any significance in the chaotic Earth climate system nor is CO2 produced by man a perturbation that would yield any predictive ability.

My confidence in climate modelers is inversely proportional to the confidence I see them show in this body that has proven to be agenda - driven and which obviously has a vested interest in what, if anything, predictive models do with cloud feedback.

When reality fails to match the models, which produce, despite millions of lines of code, little more than a lagged rescaling of the inputs, and which, with their copious parameters, have become over-fit, then either reality is adjusted by unjustified manipulations of past temperature data, or new explanations (excuses) for why the models have no predictive skill are invented.

McArdle appears reluctant to embrace the predictions of climate models under the assumption that they are similar to mid-century macroeconomic models, for which «only the unflappable true believers place great weight on their predictive ability» these days.

-- since these models have no predictive skill on a 1 yr time horizon, which means we can't run normal stats on them, and the mean drifts don't match reality over the long term, what good are the models -(seriously?)

Your comments about poor predictive models leading to so much greater need for preventative action coupled with comments about unstable systems which come and go explosively (nuclear detonations) reminded me of some cold war behaviors.

Now according to the «GCM's have no predictive value and can be tuned to any result that you want» hypothesis, climate scientists should have produced model results which showed a cooling troposphere.

«We conclude that extreme climatic events are key drivers of biodiversity patterns and that the frequency and intensity of such episodes have major implications for predictive models of species distribution and ecosystem structure, which are largely based on gradual warming trends.»

The world's climate is way too complex... with way too many significant global and regional variables (e.g., solar, volcanic and geologic activity, variations in the strength and path of the jet stream and major ocean currents, the seasons created by the tilt of the earth, and the concentration of water vapor in the atmosphere, which by the way is many times more effective at holding heat near the surface of the earth than is carbon dioxide, a non-toxic, trace gas that all plant life must have to survive, and that produce the oxygen that WE need to survive) to consider for any so - called climate model to generate a reliable and reproducible predictive model.

The statistical testing of a predictive model features a comparison of predicted to the observed relative frequencies of the various possible outcomes in the observed events that belong to a statistical sample which was drawn from the underlying population.

It would be nice, but it is not necessary to make progress and be able to produce a model which gives predictive power.

We find a close agreement between the CESM - based hindcasts and the Markov model, indicating that the largest contribution to the predictive skill of soil water on interannual to decadal timescales in CESM can be attributed to the damped persistence, which is partly governed by the evapotranspiration (Delworth and Manabe 1988), the total runoff, and the diffusion of soil moisture into the deeper soil levels as shown in the Eq.

The extent to which the models can make reasonable predictions of that functional form is evidence that they have genuine predictive power.

Jiacan Yuan is a climatologist who is interested in understanding the fundamental dynamical processes in the atmosphere and improving climate models, which could give us better predictive power and risk assessment of the changing climate.

Okay, you start by claiming that other models, which people have actually taken the time to implement in reality rather than in fantasy, have no predictive skill.

(xvii) coordinate on the development of quantitative models, predictive mapping products, and forecasts to anticipate the various pathways through which climate change may affect public health as an issue of national security.

His 2012 campaign hired «predictive modeling and data mining scientists,» according to job advertisements, which read: «Modeling analysts are charged with predicting the behavior of the American elemodeling and data mining scientists,» according to job advertisements, which read: «Modeling analysts are charged with predicting the behavior of the American eleModeling analysts are charged with predicting the behavior of the American electorate.