Sentences with phrase «by model biases»

Not exact matches

Kunal is an astute student of money and human cognitive biases, he builds his models by leveraging the fact that human beings are visibly irrational, especially in a group / tribe format.

The other problem that he argues is exacerbated by mass surveillance ad - targeting online business models is filter bubbles — aka the strategy of platforms using people's own biases as a tactic to keep them clicking by reductively feeding them more of the same stuff.

The convergence model represents human communication as a dynamic, cyclical process over time, characterized by (1) mutual causation rather than one - way mechanistic causation, and emphasizing (2) the interdependent relationship of the participants, rather than a bias toward either the gisource» or the «receiver» of «messages.»

The Christian Century's series, by example and not by intent, continues by and large to hold up this truncated model of a less - than - critical theology which proceeds without much awareness of its own class bias.

I think that there is more, as I spoke to before, there are prejudice — prejudices and bias that relate to hierarchical views by a really a paradigm or model of thinking about how we view birth.

Fixed - effect models are reported throughout, because these reflect only the random error within each study and are less affected by small study bias (usually the result of selective publication of small studies with extreme results)(39).

«Though we know many of the kinds of biases that can occur, modeling them has to occur on a sample - by - sample basis,» he added.

Using 19 climate models, a team of researchers led by Professor Minghua Zhang of the School of Marine and Atmospheric Sciences at Stony Brook University, discovered persistent dry and warm biases of simulated climate over the region of the Southern Great Plain in the central U.S. that was caused by poor modeling of atmospheric convective systems — the vertical transport of heat and moisture in the atmosphere.

FMI has been involved in research project, which evaluated the simulations of long - range transport of BB aerosol by the Goddard Earth Observing System (GEOS - 5) and four other global aerosol models over the complete South African - Atlantic region using Cloud - Aerosol Lidar with Orthogonal Polarization (CALIOP) observations to find any distinguishing or common model biases.

This gives a high level of flexibility for the search algorithm as well, because both general (i.e. free rotation and translation) and more specific moves (i.e. adding a new structure element to an existing model in the membrane plane) are allowed and biased by probability.

By using measurements collected from the U.S. DOE ARM's SGP sites and other available sources, this study shows that all participating models simulate excessive net shortwave and longwave fluxes at the surface, but with no consistent mean bias sign in turbulent fluxes over the Central U.S. and SGP.

This ordinal outcome did not appear to be continuous as required by a linear model and suggested the possibility of analytical bias.

Our «biased» profiling is based on an in vitro model of mouse terminally differentiated myotubes, induced to re-enter the cell cycle by the E1A oncogene (23).

The results of this approach may also be biased in favor of schools serving more advantaged students if the test - score growth of disadvantaged students differs in ways not captured by the value - added model.

If the measures are insufficient and the academic growth of disadvantaged students is lower than that of more advantaged students in ways not captured by the model, the one - step value - added approach will be biased in favor of high - SES schools at the expense of low - SES schools.

Although the results could differ in other settings, our method of using natural teacher turnover to evaluate bias in VA estimates can be easily implemented by school districts to evaluate the accuracy of their VA models.

To minimize bias from student sorting by instructors, I will use a course - set fixed effect model that compares between students who take exactly the same set of courses during their first semester of college enrollment; I will further augment the model by combining it with an instrumental variable approach which exploits term - by - term fluctuations in faculty composition in each department, therefore controlling for both between - and within - course sorting.

Model vulnerability by publicly discussing her work to become more aware of her own identity, privilege, and biases.

More specifically, the district and its teachers are not coming to an agreement about how they should be evaluated, rightfully because teachers understand better than most (even some VAM researchers) that these models are grossly imperfect, largely biased by the types of students non-randomly assigned to their classrooms and schools, highly unstable (i.e., grossly fluctuating from one year to the next when they should remain more or less consistent over time, if reliable), invalid (i.e., they do not have face validity in that they often contradict other valid measures of teacher effectiveness), and the like.

Their research explored whether there was evidence of this kind of bias by conducting what researchers call a «sensitivity analysis» to test whether the results from the L.A. Times model were valid and reliable.

The MRA rear wheel - drive biased platform and the engine line - up currently featured by the C - Class family will be inherited by the new model with no notable changes.

The sporty nature of the BMW M Performance model is enhanced by the rear biased set - up of the BMW xDrive all - wheel drive and the Performance Control function.

Both models retain all - wheel drive, with a 69 - percent bias towards the rear axle, and they ride on steel springs supported by active dampers, controlling the four - link front and five - link rear suspension systems.

Chrysler 300S AWD and 300C Platinum AWD models benefit even more as Sport mode turns AWD «on» (if off) and enables rear - biased torque for improved dynamics Both «S» gear and «Sport» button provide blistering - quick gear changes, reducing shift times by 37 percent (250 milliseconds versus 400 milliseconds) and can hold the desired gear without unexpected shifts, including at the redline

As it also comes with a 4Matic all - wheel drive system massaged by AMG to have an even more pronounced rear - biased torque split, the new C - Class model is following in the footsteps of the Audi S4 in terms of all - weather performance.

There are arguments for both models; proponents of the fee - charging model (most debt management companies) will say they provide better service and that the advice given by non-fee-charging organisations is likely to be biased towards Debt Management due to the way they are funded.

Big rallies within bull markets (as predicted by our model) have a bullish bias.

Because stocks have an upside bias and our models are slow moving, there is often not much profit from short positions by the time you enter and exit.

«By comparing the response of clouds and water vapor to ENSO forcing in nature with that in AMIP simulations by some leading climate models, an earlier evaluation of tropical cloud and water vapor feedbacks has revealed two common biases in the models: (1) an underestimate of the strength of the negative cloud albedo feedback and (2) an overestimate of the positive feedback from the greenhouse effect of water vapoBy comparing the response of clouds and water vapor to ENSO forcing in nature with that in AMIP simulations by some leading climate models, an earlier evaluation of tropical cloud and water vapor feedbacks has revealed two common biases in the models: (1) an underestimate of the strength of the negative cloud albedo feedback and (2) an overestimate of the positive feedback from the greenhouse effect of water vapoby some leading climate models, an earlier evaluation of tropical cloud and water vapor feedbacks has revealed two common biases in the models: (1) an underestimate of the strength of the negative cloud albedo feedback and (2) an overestimate of the positive feedback from the greenhouse effect of water vapor.

Of course, deniers will immediately recognize that Gavin's choice of smooth versus chunky peanut butter, and red versus black ants, and odd versus even numbered dominoes, all biased the model towards a preplanned warming trend, as later confirmed by his personal text messages, to be released on WikiLeaks in coming months.

Interestingly, the long - term variations indicated by the model simulations compared remarkably well with those documented by the tree - ring reconstruction, showing no obvious sign of the potential biases in the estimated low - frequency temperature variations that have been the focus of much previous work (see e.g. this previous RealClimate review).

With respect to modeling, it is a great tool for finding the right questions to ask, but by their very definition can not provide answers since a model always has the possibility of carrying the modeller's biases and blind spots.

This Nature Climate Change paper concluded, based purely on simulations by the GISS - E2 - R climate model, that estimates of the transient climate response (TCR) and equilibrium climate sensitivity (ECS) based on observations over the historical period (~ 1850 to recent times) were biased low.

And it was not an input error propagated, but a theory - bias error; one made by the models themselves and therefore present in every simulation step.

My impression from outside is that the statistical analyses are weak, the climate models are simplistic and overinfluenced by selection and publication biases, the theoretic underpinning is extraordinarily shakey and the belief engine is overrevved with the popularity of certain «star performers» and the Romantic desire for a Paradise Lost that never existed.

The author's points on non-linearity and time delays are actually more relevant to the discussion in other presentations when I talked about whether the climate models that show high future sensitivities to CO2 are consistent with past history, particularly if warming in the surface temperature record is exaggerated by urban biases.

Holland said that he recognizes that there's a potential that the study's model data might be biased by beginning the first 10 - year period in 1995, when hurricane activity ramped up rapidly.

The impact of sea surface temperature bias was further investigated by using uncoupled atmospheric models with prescribed sea surface temperatures, and those 3 models each with differing complexity showed less severe double ITCZ bias than the ensemble of coupled models.

VS04 based this conclusion on experiments using a simulation of the GKSS coupled model (similar experiments described by VS04 using an alternative simulation of the HadCM3 coupled model showed little such bias).

By 2015 and especially 2020, it will be obvious to anyone with a brain that the Alarmists have got it wrong, as the climate continues not to play along with their simplistic, biased computer models.

The models» errors are not random — as often above as below observed temperatures, and by similar magnitudes — but clearly biased, consistently above observed temperatures.

``... since uncertainty is a structural component of climate and hydrological systems, Anagnostopoulos et al. (2010) found that large uncertainties and poor skill were shown by GCM predictions without bias correction... it can not be addressed through increased model complexity....

Each year, the June — September forecasts simulated by the operational model of the India Meteorological Department seem to have a «dry bias» over the Ganga basin, predicting less rain will fall than actually does.

A recent study by Cowtan et al. (paper here) suggests that accounting for these biases between the global temperature record and those taken from climate models reduces the divergence in trend between models and observations since 1975 by over a third.

The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large - eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme.

It leads to selection bias, and it often (as in the example above) is most strongly constrained by models that are not consistent with data.

Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role.

And in that sense, a climate model is nothing more or less than a conceptual model, necessary to give a frame of reference to the state of the real world, which can never be generated by observations alone (which are incomplete, may be inconsistent, contradicting each other, biased, non-representative,...).

The implication of this optical depth bias that owes its source to biases in both the LWP and particle sizes is that the solar radiation reflected by low clouds is significantly enhanced in models compared to real clouds.

The consequence is that this bias artificially suppresses the low cloud optical depth feedback in models by almost a factor of four and thus its potential role as a negative feedback.