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PubMed2002

Uncertainty by choice: anesthesia and the children of night.

Anesthesiologists sometimes have difficulty discussing uncertainties with patients. The widespread and deeply visceral uncertainty about sleep, dreams, and death--the daily terrain of the anesthesiologist--has its roots in the classical representations of these states as siblings, the children of the goddess Night. The symbolism of mythology can guide the practitioner by recognizing, through allegory, the range of our own and our patients' fears.

Anesthesia↗
PubMed2001

How to calculate lead concentration and concentration uncertainty in XRF in vivo bone lead analysis.

The authors provide a substantial correction for calculating estimates of lead concentration and uncertainty for in vivo X-ray fluorescent bone analysis with Cd-109 source. Based on general principles, they provide mathematical techniques for propagation of uncertainties in XRF analysis. They give additional considerations for lowering the detection limit and improving spectral data quality.

Biometry↗
PubMedDate not supplied

An improvement of uncertainty in activity standardization with efficiency tracer technique.

The activities of ten pure beta emitters were measured with two tracer nuclei for each one by using efficiency tracing technique. The determination results of specific activity of 35S, 63Ni and 185W, using efficiency tracers 60Co and 134Cs, are presented. The uncertainties of the final results for the three beta emitting nuclides were 0.5% at 99.7% confidence. The relationship between beta spectra and efficiency for the five nuclides were calculated with Fermi theory. The effects of the beta spectra shapes, end-point energies and chemical form of the tracers on the beta emitter activity results have been re-investigated. The type B uncertainty introduced by the upper limit of the fitting region (corresponding to the beta low detection efficiency), the polynomial fitting power (60Co as tracer), the lower limit of the fitting region (corresponding to self-absorption) and the gamma gate setting (134Cs as tracer) were investigated.

Journal Article↗
PubMed2002

Evaluation of uncertainties in 90Sr-body-burdens obtained by whole-body count: application of Bayes' rule to derive detection limits by analysis of a posteriori data.

A whole body counter (WBC) designed to measure bremsstrahlung from 90Y, the short-lived daughter of 90Sr, has been used since 1974 to measure 90Sr-body burdens in residents along the Techa River, which was contaminated by releases from the Mayak Production Association. Bayes' rule has been applied to the a posteriori WBC data in order to derive the uncertainties associated with the data: The lower limit of reliable detection is 2.0 kBq and the uncertainty of routine measurements is 1.6 kBq.

Bayes Theorem↗
PubMed2003

Corrections to "How to calculate lead concentration and concentration uncertainty in XRF in vivo bone lead analysis" by Kondrashov and Rothenberg.

Kondrashov and Rothenberg (Appl. Radiat. Isot. 55 (2001) 799) have published "a substantial correction for calculating estimates of lead concentration and uncertainty for in vivo X-ray fluorescent bone analysis with Cd-109 source" (sic). Our paper shows that their correction fails to consider two important points that render it (i) a correction to a superseded method and (ii) of limited effect. Also, their approach to a "crude" estimate produces measurement uncertainties that are implausibly small. In order that they not be propagated in the literature, our paper also corrects several misstatements and errors in Kondrashov and Rothenberg.

Analysis of Variance↗
PubMed1999

Dose uncertainties for large solar particle events: input spectra variability and human geometry approximations.

The true uncertainties in estimates of body organ absorbed dose and dose equivalent, from exposures of interplanetary astronauts to large solar particle events (SPEs), are essentially unknown. Variations in models used to parameterize SPE proton spectra for input into space radiation transport and shielding computer codes can result in uncertainty about the reliability of dose predictions for these events. Also, different radiation transport codes and their input databases can yield significant differences in dose predictions, even for the same input spectra. Different results may also be obtained for the same input spectra and transport codes if different spacecraft and body self-shielding distributions are assumed. Heretofore there have been no systematic investigations of the variations in dose and dose equivalent resulting from these assumptions and models. In this work we present a study of the variability in predictions of organ dose and dose equivalent arising from the use of different parameters to represent the same incident SPE proton data and from the use of equivalent sphere approximations to represent human body geometry. The study uses the BRYNTRN space radiation transport code to calculate dose and dose equivalent for the skin, ocular lens and bone marrow using the October 1989 SPE as a model event. Comparisons of organ dose and dose equivalent, obtained with a realistic human geometry model and with the oft-used equivalent sphere approximation, are also made. It is demonstrated that variations of 30-40% in organ dose and dose equivalent are obtained for slight variations in spectral fitting parameters obtained when various data points are included or excluded from the fitting procedure. It is further demonstrated that extrapolating spectra from low energy (< or = 30 MeV) proton fluence measurements, rather than using fluence data extending out to 100 MeV results in dose and dose equivalent predictions that are underestimated by factors as large as 2-3. Finally, it is also demonstrated that the use of equivalent sphere approximations to represent body organ self-shielding distributions results in organ doses and dose equivalent predictions that are 2-3 times larger than values obtained with anthropomorphic shielding configurations.

Aluminum↗
PubMed2004

Uncertainty analysis in a mechanistic model of bacterial regrowth in distribution systems.

The first generation of mechanistic models of bacterial regrowth in distribution systems (DS) provides insight into cause-and-effect relationships. However, the state of knowledge about the processes included in these models is insufficient to warrant deterministic predictions. Even if the process descriptions are reasonable, the uncertainty in values of key system constants limits predictions of bacterial growth. A new mechanistic model was developed to incorporate the accepted knowledge of physical, chemical, and biological processes with the hydraulic features in order to capture the unsteady state behavior of the DS. Sensitivitytesting showed that the extent of bacterial regrowth was affected mainly by the rate constants for chlorine decay reactions in bulk water and on the pipe wall and by the maximum growth rate constant of attached bacteria. A simple hypothetical network was used to evaluate the effects of uncertainty in these three system constants by running 100 Monte Carlo simulations. Cumulative probability plots showed a wide range of predictions for concentrations of bacteria and chlorine in bulk water at various nodes in the DS. The magnitude of these concentrations and the range of values were greatly affected by water residence time to each node. Once the chlorine residual is depleted, bacterial growth is mainly influenced by the amount of substrate available. However, high values of the coefficients for the maximum growth rate of attached bacteria, the chlorine decay in bulk water, and the chlorine decay by wall reaction did not necessarily lead to the maximum bacterial growth at a given location.

Bacteria↗
PubMed1999

Evaluation of the uncertainty in an oral reference dose for methylmercury due to interindividual variability in pharmacokinetics.

An analysis of the uncertainty in guidelines for the ingestion of methylmercury (MeHg) due to human pharmacokinetic variability was conducted using a physiologically based pharmacokinetic (PBPK) model that describes MeHg kinetics in the pregnant human and fetus. Two alternative derivations of an ingestion guideline for MeHg were considered: the U.S. Environmental Protection Agency reference dose (RfD) of 0.1 microgram/kg/day derived from studies of an Iraqi grain poisoning episode, and the Agency for Toxic Substances and Disease Registry chronic oral minimal risk level (MRL) of 0.5 microgram/kg/day based on studies of a fish-eating population in the Seychelles Islands. Calculation of an ingestion guideline for MeHg from either of these epidemiological studies requires calculation of a dose conversion factor (DCF) relating a hair mercury concentration to a chronic MeHg ingestion rate. To evaluate the uncertainty in this DCF across the population of U.S. women of child-bearing age, Monte Carlo analyses were performed in which distributions for each of the parameters in the PBPK model were randomly sampled 1000 times. The 1st and 5th percentiles of the resulting distribution of DCFs were a factor of 1.8 and 1.5 below the median, respectively. This estimate of variability is consistent with, but somewhat less than, previous analyses performed with empirical, one-compartment pharmacokinetic models. The use of a consistent factor in both guidelines of 1.5 for pharmacokinetic variability in the DCF, and keeping all other aspects of the derivations unchanged, would result in an RfD of 0.2 microgram/kg/day and an MRL of 0.3 microgram/kg/day.

Adult↗
PubMed1999

Quantifying uncertainty in a risk assessment using human data.

A call for risk assessment approaches that better characterize and quantify uncertainty has been made by the scientific and regulatory community. This paper responds to that call by demonstrating a distributional approach that draws upon human data to derive potency estimates and to identify and quantify important sources of uncertainty. The approach is rooted in the science of decision analysis and employs an influence diagram, a decision tree, probabilistic weights, and a distribution of point estimates of carcinogenic potency. Its results estimate the likelihood of different carcinogenic risks (potencies) for a chemical under a specific scenario. For this exercise, human data on formaldehyde were employed to demonstrate the approach. Sensitivity analyses were performed to determine the relative impact of specific levels and alternatives on the potency distribution. The resulting potency estimates are compared with the results of an exercise using animal data on formaldehyde. The paper demonstrates that distributional risk assessment is readily adapted to situations in which epidemiologic data serve as the basis for potency estimates. Strengths and weaknesses of the distributional approach are discussed. Areas for further application and research are recommended.

Carcinogens↗
PubMed1998

Propagation of experimental uncertainties using the Lipari-Szabo model-free analysis of protein dynamics.

In this paper we make use of the graphical procedure previously described [Jin, D. et al. (1997) J. Am. Chem. Soc., 119, 6923-6924] to analyze NMR relaxation data using the Lipari-Szabo model-free formalism. The graphical approach is advantageous in that it allows the direct visualization of the experimental uncertainties in the motional parameter space. Some general 'rules' describing the relationship between the precision of the relaxation measurements and the precision of the model-free parameters and how this relationship changes with the overall tumbling time (tau m) are summarized. The effect of the precision in the relaxation measurements on the detection of internal motions not close to the extreme narrowing limit is analyzed. We also show that multiple timescale internal motions may be obscured by experimental uncertainty, and that the collection of relaxation data at very high field strength can improve the ability to detect such deviations from the simple Lipari-Szabo model.

Models, Theoretical↗
PubMed2004

Insulin minimal model indexes and secretion: proper handling of uncertainty by a Bayesian approach.

The identification of the insulin minimal model (MM) for the estimation of insulin secretion rate (ISR) and physiological indexes (e.g. beta-cell sensitivity) requires the knowledge of C-peptide (CP) kinetics. The four parameters of the two-compartment model of CP kinetics in a given individual can be derived either from an additional bolus experiment or, more frequently, from a population model. However, in both situations, the CP kinetics is uncertain and, in MM identification, it should be treated as such. This paper shows how to handle CP kinetics uncertainty by using a Bayesian methodology. In seven subjects, MM indexes and ISR were estimated together with their confidence intervals, using either the bolus data or the population model to assess CP kinetics. The two main results that arise from the application of the new methodology are: (i) the use of the population model in place of the bolus data to determine CP kinetics does not affect, on average, the point estimates of ISR profile and MM parameters but only the confidence intervals which becomes wider (less than 50%); (ii) in both the bolus and population situation neglecting the uncertainty of CP kinetics, as done in MM literature so far, introduces no bias, on average, on point estimates of MM indexes but only an underestimation of confidence intervals.

Adult↗
PubMed1994

Individual differences in causal uncertainty.

This article presents a scale that measures chronic individual differences in people's uncertainty about their ability to understand and detect cause-and-effect relationships in the social world: the Causal Uncertainty Scale (CUS). The results of Study 1 indicated that the scale has good internal and adequate test-retest reliability. Additionally, the results of a factor analysis suggested that the scale appears to be tapping a single construct. Study 2 examined the convergent and discriminant validity of the scale, and Studies 3 and 4 examined the predictive and incremental validity of the scale. The importance of the CUS to work on depressives' social information processing and for basic research and theory on human social judgment processes is discussed.

Adult↗
PubMed1985

Decision making under uncertainty: a comparison of simple scalability, fixed-sample, and sequential-sampling models.

The purpose of this article is to investigate the learning and memory processes involved in decision making under uncertainty. In two different experiments, subjects were given a choice between a certain alternative that produced a single known payoff and an uncertain alternative that produced a normal distribution of payoffs. Initially this distribution was unknown, and in the first experiment it was learned through feedback from past decisions, whereas in the second experiment it was learned by observing sample outcomes. In the first experiment, a response deadline was used to limit the amount of time available for making a decision. In the second experiment, an observation cost was used to limit the number of samples that could be purchased. The mean and variance of the uncertain alternative and the value of the certain alternative were factorially manipulated to study their joint effects on choice probability, choice response time (Experiment 1), and number of observations purchased (Experiment 2). Algebraic-deterministic theories developed for decision making with simple gambles fail to explain the present results. Two new models are developed and tested--fixed- and sequential-sampling models--that attempt to describe the learning and memory processes involved in decision making under uncertainty.

Adult↗
PubMed1990

The influence of uncertainty and premovement visual information on manual aiming.

Target-aiming studies in which premovement visual information is manipulated suggest that when vision is occluded, a brief visual representation of the target environment may be used to guide movement. The purpose of this work was to determine if the internal representation contains information about the whole movement environment or just specific information about the position of a single target goal. Two experiments were conducted in which we manipulated both target uncertainty and the visual information available before and during a target-aiming movement. Radial error differences between visual conditions and the independence of the vision and uncertainty manipulations support the hypothesis that subjects form a representation of the overall movement environment.

Adult↗
PubMed2000

Quantifying the uncertainty in forecasts of anthropogenic climate change

Forecasts of climate change are inevitably uncertain. It is therefore essential to quantify the risk of significant departures from the predicted response to a given emission scenario. Previous analyses of this risk have been based either on expert opinion, perturbation analysis of simplified climate models or the comparison of predictions from general circulation models. Recent observed changes that appear to be attributable to human influence provide a powerful constraint on the uncertainties in multi-decadal forecasts. Here we assess the range of warming rates over the coming 50 years that are consistent with the observed near-surface temperature record as well as with the overall patterns of response predicted by several general circulation models. We expect global mean temperatures in the decade 2036-46 to be 1-2.5 K warmer than in pre-industrial times under a 'business as usual' emission scenario. This range is relatively robust to errors in the models' climate sensitivity, rate of oceanic heat uptake or global response to sulphate aerosols as long as these errors are persistent over time. Substantial changes in the current balance of greenhouse warming and sulphate aerosol cooling would, however, increase the uncertainty. Unlike 50-year warming rates, the final equilibrium warming after the atmospheric composition stabilizes remains very uncertain, despite the evidence provided by the emerging signal.

Journal Article↗
PubMed2004

Biodiversity conservation: uncertainty in predictions of extinction risk.

Thomas et al. model species-distribution responses to a range of climate-warming scenarios and use a novel application of the species-area relationship to estimate that 15-37% of modelled species in various regions of the world will be committed to extinction by 2050. Although we acknowledge the efforts that they make to measure the uncertainties associated with different climate scenarios, species' dispersal abilities and z values (predictions ranged from 5.6% to 78.6% extinctions), we find that two additional sources of uncertainty may substantially increase the variability in predictions.

Adaptation, Physiological↗
PubMed2005

Uncertainty in predictions of the climate response to rising levels of greenhouse gases.

The range of possibilities for future climate evolution needs to be taken into account when planning climate change mitigation and adaptation strategies. This requires ensembles of multi-decadal simulations to assess both chaotic climate variability and model response uncertainty. Statistical estimates of model response uncertainty, based on observations of recent climate change, admit climate sensitivities--defined as the equilibrium response of global mean temperature to doubling levels of atmospheric carbon dioxide--substantially greater than 5 K. But such strong responses are not used in ranges for future climate change because they have not been seen in general circulation models. Here we present results from the 'climateprediction.net' experiment, the first multi-thousand-member grand ensemble of simulations using a general circulation model and thereby explicitly resolving regional details. We find model versions as realistic as other state-of-the-art climate models but with climate sensitivities ranging from less than 2 K to more than 11 K. Models with such extreme sensitivities are critical for the study of the full range of possible responses of the climate system to rising greenhouse gas levels, and for assessing the risks associated with specific targets for stabilizing these levels.

Journal Article↗
PubMed1997

The concept of uncertainty as applied to chemical measurements.

The calculation of uncertainty as recommended for physical measurements cannot be transferred readily to chemical measurements. Physical measurements and chemical measurements have entirely different error patterns that behave differently on replication. Correctable local bias predominates in physical systems and random error is minor; random error predominates in chemical systems and bias is difficult to identify and eradicate. Therefore bias must be monitored by randomizing in the interlaboratory environment, a concept not handled by the conventional ISO treatment of uncertainty.

Chemistry Techniques, Analytical↗