Sentences with phrase «large uncertainties in the data»

I also agree that my calculations above have ignored the large uncertainty in the data.

It is almost impossible to quantify that fraction, however, because of the large uncertainties in the data and the lack of a useful computable theory.

The report authors noted large uncertainties in the data persist and the true growth figure may be anywhere between 1 and 3 %.

Not exact matches

These risks and uncertainties include: Gilead's ability to achieve its anticipated full year 2018 financial results; Gilead's ability to sustain growth in revenues for its antiviral and other programs; the risk that private and public payers may be reluctant to provide, or continue to provide, coverage or reimbursement for new products, including Vosevi, Yescarta, Epclusa, Harvoni, Genvoya, Odefsey, Descovy, Biktarvy and Vemlidy ®; austerity measures in European countries that may increase the amount of discount required on Gilead's products; an increase in discounts, chargebacks and rebates due to ongoing contracts and future negotiations with commercial and government payers; a larger than anticipated shift in payer mix to more highly discounted payer segments and geographic regions and decreases in treatment duration; availability of funding for state AIDS Drug Assistance Programs (ADAPs); continued fluctuations in ADAP purchases driven by federal and state grant cycles which may not mirror patient demand and may cause fluctuations in Gilead's earnings; market share and price erosion caused by the introduction of generic versions of Viread and Truvada, an uncertain global macroeconomic environment; and potential amendments to the Affordable Care Act or other government action that could have the effect of lowering prices or reducing the number of insured patients; the possibility of unfavorable results from clinical trials involving investigational compounds; Gilead's ability to initiate clinical trials in its currently anticipated timeframes; the levels of inventory held by wholesalers and retailers which may cause fluctuations in Gilead's earnings; Kite's ability to develop and commercialize cell therapies utilizing the zinc finger nuclease technology platform and realize the benefits of the Sangamo partnership; Gilead's ability to submit new drug applications for new product candidates in the timelines currently anticipated; Gilead's ability to receive regulatory approvals in a timely manner or at all, for new and current products, including Biktarvy; Gilead's ability to successfully commercialize its products, including Biktarvy; the risk that physicians and patients may not see advantages of these products over other therapies and may therefore be reluctant to prescribe the products; Gilead's ability to successfully develop its hematology / oncology and inflammation / respiratory programs; safety and efficacy data from clinical studies may not warrant further development of Gilead's product candidates, including GS - 9620 and Yescarta in combination with Pfizer's utomilumab; Gilead's ability to pay dividends or complete its share repurchase program due to changes in its stock price, corporate or other market conditions; fluctuations in the foreign exchange rate of the U.S. dollar that may cause an unfavorable foreign currency exchange impact on Gilead's future revenues and pre-tax earnings; and other risks identified from time to time in Gilead's reports filed with the U.S. Securities and Exchange Commission (the SEC).

However, there are large uncertainties in the estimate and it appears it is not compatible with the satellite «handshake» data transmitted from the aircraft, which is currently considered the most reliable source of information.

A new integrated climate model developed by Oak Ridge National Laboratory and other institutions is designed to reduce uncertainties in future climate predictions as it bridges Earth systems with energy and economic models and large - scale human impact data.

A new integrated computational climate model developed to reduce uncertainties in future climate predictions marks the first successful attempt to bridge Earth systems with energy and economic models and large - scale human impact data.

When differences in scaling between previous studies are accounted for, the various current and previous estimates of NH mean surface temperature are largely consistent within uncertainties, despite the differences in methodology and mix of proxy data back to approximately A.D. 1000... Conclusions are less definitive for the SH and globe, which we attribute to larger uncertainties arising from the sparser available proxy data in the SH.

[Response: But you have ignored the uncertainty in the data — which is much larger than this.

However, you have to factor in a larger uncertainty in the earlier data... — gavin]

In the end, I would hypothesize that the result of the freeing of data and code will necessarily lead to a more robust understanding of scientific uncertainties, which may have the perverse effect of making the future less clear, i.e., because it will result in larger error bars around observed temperature trends which will carry through into the projectionIn the end, I would hypothesize that the result of the freeing of data and code will necessarily lead to a more robust understanding of scientific uncertainties, which may have the perverse effect of making the future less clear, i.e., because it will result in larger error bars around observed temperature trends which will carry through into the projectionin larger error bars around observed temperature trends which will carry through into the projections.

The IPCC range, on the other hand, encompasses the overall uncertainty across a very large number of studies, using different methods all with their own potential biases and problems (e.g., resulting from biases in proxy data used as constraints on past temperature changes, etc.) There is a number of single studies on climate sensitivity that have statistical uncertainties as small as Cox et al., yet different best estimates — some higher than the classic 3 °C, some lower.

Some compromises between inconsistent data mean that... [the fluxes] are not always exactly consistent: errors of ~ 15 % may be present in the fluxes for nuclei and protons: the uncertainties for electrons are much larger.»

If you are going to leave off the last two data points as their uncertainty is too large, you may also want to leave out some of the earlier plot points as well (especially in the early 1800's).

Previous large natural oscillations are important to examine: however, 1) our data isn't as good with regards to external forcings or to historical temperatures, making attribution more difficult, 2) to the extent that we have solar and volcanic data, and paleoclimate temperature records, they are indeed fairly consistent with each other within their respective uncertainties, and 3) most mechanisms of internal variability would have different fingerprints: eg, shifting of warmth from the oceans to the atmosphere (but we see warming in both), or simultaneous warming of the troposphere and stratosphere, or shifts in global temperature associated with major ocean current shifts which for the most part haven't been seen.

For the coverage uncertainty on the global average to be significantly larger would require the variability in the nineteenth century data gaps to be much larger than in the well observed period.

After the 1960s bias uncertainties dominate the total and are by far the largest component of the uncertainty in the most recent data.

«In spite of the large uncertainties, the data that are available portray a rather consistent picture of a cryosphere in decline over the 20th century, increasingly so during 1993 to 2003.&raquIn spite of the large uncertainties, the data that are available portray a rather consistent picture of a cryosphere in decline over the 20th century, increasingly so during 1993 to 2003.&raquin decline over the 20th century, increasingly so during 1993 to 2003.»

The use of even more recently computer - reconstructed total solar irradiance data (whatever have large uncertainties) for the period prior to 1976 would not change any of the conclusions in my paper, where quantitative analyses were emphasized on the influences of humans and the Sun on global surface temperature after 1970 when direct measurements became available.

Quite simply, contrary to Briggs» claims, the warming trend is much larger than the uncertainty in the data.

To estimate the uncertainty range (2σ) for mean tropical SST cooling, we consider the error contributions from (a) large - scale patterns in the ocean data temperature field, which hamper a direct comparison with a coarse - resolution model, and (b) the statistical error for each reconstructed paleo - temperature value.

The station data coverage in this region is poor for the E-OBS, which contributes to a relatively large uncertainty in precipitation and temperature estimates for this region in the E-OBS dataset.

It is important to note that significant uncertainty exists in radiosonde datasets reflecting the large number of choices available to researchers in their construction and the many heterogeneities in the data.

In contrast, the longer term fitted to HadSST3 is twice that found in the original data (circa 350 years) with a somewhat larger uncertainty and parameters incompatible with the results for ICOADIn contrast, the longer term fitted to HadSST3 is twice that found in the original data (circa 350 years) with a somewhat larger uncertainty and parameters incompatible with the results for ICOADin the original data (circa 350 years) with a somewhat larger uncertainty and parameters incompatible with the results for ICOADS.

Large adjustments to the raw data, and substantial changes in successive data set versions, imply substantial uncertainties.

Furthermore, on these times scales the differences between MSU data sets are often not larger than published internal uncertainty estimates for the RSS product alone and therefore may not be statistically significant when the internal uncertainty in each data set is taken into account.

I frankly doubt that this model can be extrapolated into either the past or the future, and the data uncertainties are so large (and almost certainly underestimated and / or systematically biased in HadCRUT4) that the sensitivity could easily be either larger or smaller than the best fit observed here — if you like, I get a TCS of around 1.8 C plus or minus maybe a whole degree.

and «no data or computer code appears to be archived in relation to the paper» and «the sensitivity of Shindell's TCR estimate to the aerosol forcing bias adjustment is such that the true uncertainty of Shindell's TCR range must be huge — so large as to make his estimate worthless» and the seemingly arbitrary to cherry picked climate models used in Shindell's analysis.

Despite uncertainty and confusion about the numbers, the 2016 data is one more piece of evidence that China will not return to the days of skyrocketing coal consumption for good, and that the world's largest CO2 emitter is on the right path to start reducing its emissions permanently at some point in the coming decade.

• There have been fluctuations in the number of tropical storms and hurricanes from decade to decade, and data uncertainty is larger in the early part of the record compared to the satellite era beginning in 1965.

On his blog, tamino does the statistical analysis of the BEST data and finds that because the timeframe in question is so short, the uncertainty is too large to say for certain that the short - term trend in question is any different than the long - term trend.

In other words, April and May 2010 should be excluded from BEST data analysis because they are incomplete, their uncertainties are just too large, and April 2010 is quite obviously an anomalous outlier.

Thus we have many parameters with little data to validate / differentiate them and very large uncertainties as shown in this post above.

Uncertainties in the ages of these kind of data should in general be no larger than those of the dating methods, as the natural cooling process during which the magnetisation is acquired is comparatively fast.

However, it is also apparent, that given the complex nature, and large uncertainties of the data, that a nuanced interpretation is in order.

Yet the consistency among the three compilations masks large uncertainties in the raw data on which they are based.

As it had turned out that even large - scale features of the model are rather sensitive to changes in the data set, particularly for the earlier part the model, the final model was obtained as the average of 2000 models where data and ages were varied within their uncertainty estimates and bootstraps on the final data sets were performed (hence version number 1b).

This is neither supported by the data (estimated sizes of flux), the large uncertainties and the fact that CO2 residence time in the atmosphere is very short — 5 years or so.

... the uncertainties in trend estimates using just data since 2000 are much larger than the trend estimates themselves.

The uncertainty in the annual CO2 ppM increases in the atmosphere are quite small given the indentical data coming from the large numbers of sources around the world.

The error in the corrected dataset will be larger than the error in the original data due to uncertainty in the ENSO (etc.) coefficients.

Don't know where I got my lines crossed but I herewith point out in Chapter1 figures 1.4 and 1.5, comparing near surface temperature range observed data with projections, 1990 — 2015 with its plateau of measured data warming and large uncertainty shading.

Scientific progress since the Third Assessment Report (TAR) is based upon large amounts of new and more comprehensive data, more sophisticated analyses of data, improvements in understanding of processes and their simulation in models and more extensive exploration of uncertainty ranges.

Each of the various alternative versions where these sub-networks of proxy data have been excluded fall almost entirely within the uncertainties of the full reconstruction for at least the past 1100 years, while larger discrepancies are observed further back for the reconstruction without either tree - ring data or the 7 series in question, owing to the extreme sparseness of the resulting sub-network.

Another issue is whether we have estimated the totality of uncertainty in the long - term data set used — maybe the envelope is really much larger, due to inherent characteristics of the proxy data themselves....

There are no trends in temperatures over this period and the inherent uncertainty in the data is largest at this time due to a sparser observing network.

This is where differences in data assimilation methodology and implementation create the largest analysis differences or uncertainty — which is related to future forecast error.

It is true that there are remaining large uncertainties, which are only to be expected using proxy data in scattered locations.

In fact, it's a large stretch to assume that actual OLR, as opposed to calculated OLR, varied over that large a range for the time period, given the known large uncertainty in the NCEP / NCAR reanalysis datIn fact, it's a large stretch to assume that actual OLR, as opposed to calculated OLR, varied over that large a range for the time period, given the known large uncertainty in the NCEP / NCAR reanalysis datin the NCEP / NCAR reanalysis data.

In 2004 some teams pointed out that the huge gaps and uncertainties in the pre-19th century data, and the methods used to average the data, could conceal changes of temperature in the past that might have been as large and abrupt as anything seen in modern timeIn 2004 some teams pointed out that the huge gaps and uncertainties in the pre-19th century data, and the methods used to average the data, could conceal changes of temperature in the past that might have been as large and abrupt as anything seen in modern timein the pre-19th century data, and the methods used to average the data, could conceal changes of temperature in the past that might have been as large and abrupt as anything seen in modern timein the past that might have been as large and abrupt as anything seen in modern timein modern times.