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UNLABELLED: This study evaluated lesion mislocalization between PET and CT on PET/CT studies when CT instead of germanium is used for attenuation correction (AC). METHODS: PET/CT scans were obtained for 300 clinical patients. Both CT and germanium scans were used to correct PET emission data. Cases were noted of suspected inaccurate localization of lesions on any of the 5 sets of images (PET using germanium AC [GeAC] fused and not fused with CT, PET using CT AC fused and not fused with CT, and PET with no AC [NAC]). Independent CT or MRI was used to determine true lesion locations. RESULTS: Six of 300 patients (2%) had lesion mislocalization when CT was used for AC or fusion. True liver dome lesions were mislocalized to the right lung base on PET/CT, likely because of a respiratory motion difference between PET and CT. No mislocalization was present on NAC PET or non-CT-fused GeAC PET images. CONCLUSION: Serious lesion mislocalization on PET/CT studies may occur, albeit very infrequently, when CT is used for either AC or fusion.
Background The availability of large language models such as Chat Generative Pre-trained Transformer (ChatGPT, OpenAI) has enabled individuals from diverse backgrounds to access medical information. However, concerns exist about the accuracy of ChatGPT responses and the references used to generate medical content. Methods This observational study investigated the authenticity and accuracy of references in medical articles generated by ChatGPT. ChatGPT-3.5 generated 30 short medical papers, each with at least three references, based on standardized prompts encompassing various topics and therapeutic areas. Reference authenticity and accuracy were verified by searching Medline, Google Scholar, and the Directory of Open Access Journals. The authenticity and accuracy of individual ChatGPT-generated reference elements were also determined. Results Overall, 115 references were generated by ChatGPT, with a mean of 3.8±1.1 per paper. Among these references, 47% were fabricated, 46% were authentic but inaccurate, and only 7% were authentic and accurate. The likelihood of fabricated references significantly differed based on prompt variations; yet the frequency of authentic and accurate references remained low in all cases. Among the seven components evaluated for each reference, an incorrect PMID number was most common, listed in 93% of papers. Incorrect volume (64%), page numbers (64%), and year of publication (60%) were the next most frequent errors. The mean number of inaccurate components was 4.3±2.8 out of seven per reference. Conclusions The findings of this study emphasize the need for caution when seeking medical information on ChatGPT since most of the references provided were found to be fabricated or inaccurate. Individuals are advised to verify medical information from reliable sources and avoid relying solely on artificial intelligence-generated content.
Discrimination has been widely studied in the social sciences. Economists often categorize the source of discrimination as either taste-based or statistical—a valuable distinction for policy design and welfare analysis. In this paper, we highlight that in many situations economic agents may have inaccurate beliefs, and demonstrate that the possibility of inaccurate statistical discrimination generates an identification problem for attempts to isolate the source of differential treatment. We introduce isodiscrimination curves —which represent the set of preferences and beliefs that generate the same level of discrimination—to formally outline the identification problem: when not accounted for, inaccurate statistical discrimination can be mistaken for taste-based discrimination, accurate statistical discrimination, or their combination. A review of the empirical discrimination literature in economics, spanning 1990-2018, reveals the scope of this issue. While most papers discuss and attempt to distinguish between taste and statistical discrimination, a small minority—fewer than 7%—consider inaccurate beliefs in the analysis. An experiment illustrates a methodology for differentiating between the three sources of discrimination, demonstrating the pitfalls of the identification problem while presenting a portable solution.
People routinely encounter inaccurate information, from fake news designed to confuse audiences, to communications with inadvertent mistakes, to stories made up to entertain readers. The hope is that these inaccuracies can be easily ignored, exerting little influence on our thoughts and actions. Unfortunately, being exposed to inaccuracies leads to problematic consequences. After reading inaccurate statements, readers exhibit clear effects of those contents on their decisions and problem-solving. This occurs even when readers possess appropriate prior knowledge to evaluate and reject the inaccuracies. Exposure to inaccurate information leads to confusion about what is true, doubt about accurate understandings, and subsequent reliance on falsehoods. Interventions and technologies designed to address these effects by encouraging critical evaluation can support effective comprehension and learning.
Accurate eyewitness identifications can be distinguished from erroneous ones in part by asking witnesses to describe the decision processes that led to their judgments. In 4 studies, mock witnesses were presented with a videotaped staged crime and then asked to identify the perpetrator from a photo lineup. Of those making positive identifications, accurate witnesses were more likely than their inaccurate counterparts to state that their judgments resulted from automatic recognition (e.g., «His face just 'popped out' at me»). Inaccurate witnesses more frequently stated that they followed a process of elimination strategy (e.g., «I compared the photos to each other to narrow the choices»). A 5th study revealed that people have partial understanding of these principles, and thus are modestly succesful in differentiating accurate from inaccurate identifications
Being able to evaluate the accuracy of an informant is essential to communication. Three experiments explored preschoolers' (N=119) understanding that, in cases of conflict, information from reliable informants is preferable to information from unreliable informants. In Experiment 1, children were presented with previously accurate and inaccurate informants who presented conflicting names for novel objects. 4-year-olds-but not 3-year-olds-predicted whether an informant would be accurate in the future, sought, and endorsed information from the accurate over the inaccurate informant. In Experiment 2, both age groups displayed trust in knowledgeable over ignorant speakers. In Experiment 3, children extended selective trust when learning both verbal and nonverbal information. These experiments demonstrate that preschoolers have a key strategy for assessing the reliability of information.
We demonstrate a simple greedy algorithm that can reliably recover a vector <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">v</i> ¿ ¿ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sup> from incomplete and inaccurate measurements <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</i> = ¿ <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">v</i> + <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> . Here, ¿ is a <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> x <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> measurement matrix with <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> <<d, and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> is an error vector. Our algorithm, Regularized Orthogonal Matching Pursuit (ROMP), seeks to provide the benefits of the two major approaches to sparse recovery. It combines the speed and ease of implementation of the greedy methods with the strong guarantees of the convex programming methods. For any measurement matrix ¿ that satisfies a quantitative restricted isometry principle, ROMP recovers a signal <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">v</i> with <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> ) nonzeros from its inaccurate measurements <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</i> in at most <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> iterations, where each iteration amounts to solving a least squares problem. The noise level of the recovery is proportional to ¿{log <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> } || <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> || <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> . In particular, if the error term <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> vanishes the reconstruction is exact.
The gene encoding the forkhead box transcription factor, FOXP2, is essential for developing the full articulatory power of human language. Mutations of FOXP2 cause developmental verbal dyspraxia (DVD), a speech and language disorder that compromises the fluent production of words and the correct use and comprehension of grammar. FOXP2 patients have structural and functional abnormalities in the striatum of the basal ganglia, which also express high levels of FOXP2. Since human speech and learned vocalizations in songbirds bear behavioral and neural parallels, songbirds provide a genuine model for investigating the basic principles of speech and its pathologies. In zebra finch Area X, a basal ganglia structure necessary for song learning, FoxP2 expression increases during the time when song learning occurs. Here, we used lentivirus-mediated RNA interference (RNAi) to reduce FoxP2 levels in Area X during song development. Knockdown of FoxP2 resulted in an incomplete and inaccurate imitation of tutor song. Inaccurate vocal imitation was already evident early during song ontogeny and persisted into adulthood. The acoustic structure and the duration of adult song syllables were abnormally variable, similar to word production in children with DVD. Our findings provide the first example of a functional gene analysis in songbirds and suggest that normal auditory-guided vocal motor learning requires FoxP2.
People frequently continue to use inaccurate information in their reasoning even after a credible retraction has been presented. This phenomenon is often referred to as the continued influence effect of misinformation. The repetition of the original misconception within a retraction could contribute to this phenomenon, as it could inadvertently make the "myth" more familiar-and familiar information is more likely to be accepted as true. From a dual-process perspective, familiarity-based acceptance of myths is most likely to occur in the absence of strategic memory processes. Thus, we examined factors known to affect whether strategic memory processes can be utilized: age, detail, and time. Participants rated their belief in various statements of unclear veracity, and facts were subsequently affirmed and myths were retracted. Participants then rerated their belief either immediately or after a delay. We compared groups of young and older participants, and we manipulated the amount of detail presented in the affirmative or corrective explanations, as well as the retention interval between encoding and a retrieval attempt. We found that (a) older adults over the age of 65 were worse at sustaining their postcorrection belief that myths were inaccurate, (b) a greater level of explanatory detail promoted more sustained belief change, and (c) fact affirmations promoted more sustained belief change in comparison with myth retractions over the course of 1 week (but not over 3 weeks), This supports the notion that familiarity is indeed a driver of continued influence effects. (PsycINFO Database Record
Abstract Suppose we wish to recover a vector x 0 ∈ ℝ 𝓂 (e.g., a digital signal or image) from incomplete and contaminated observations y = A x 0 + e ; A is an 𝓃 × 𝓂 matrix with far fewer rows than columns (𝓃 ≪ 𝓂) and e is an error term. Is it possible to recover x 0 accurately based on the data y ? To recover x 0 , we consider the solution x # to the 𝓁 1 ‐regularization problem where ϵ is the size of the error term e . We show that if A obeys a uniform uncertainty principle (with unit‐normed columns) and if the vector x 0 is sufficiently sparse, then the solution is within the noise level As a first example, suppose that A is a Gaussian random matrix; then stable recovery occurs for almost all such A 's provided that the number of nonzeros of x 0 is of about the same order as the number of observations. As a second instance, suppose one observes few Fourier samples of x 0 ; then stable recovery occurs for almost any set of 𝓃 coefficients provided that the number of nonzeros is of the order of 𝓃/(log 𝓂) 6 . In the case where the error term vanishes, the recovery is of course exact, and this work actually provides novel insights into the exact recovery phenomenon discussed in earlier papers. The methodology also explains why one can also very nearly recover approximately sparse signals. © 2006 Wiley Periodicals, Inc.
Abstract A gross Earth datum is a single measurable number describing some property of the whole Earth, such as mass, moment of inertia, or the frequency of oscillation of some identified elastic-gravitational normal mode. We suppose that a finite set G of gross Earth data has been measured, that the measurements are inaccurate, and that the variance matrix of the errors of measurement can be estimated. We show that some such sets G of measurements determine the structure of the Earth within certain limits of error except for fine-scale detail. That is, from some setsG it is possible to compute localized averages of the Earth structure at various depths. These localized averages will be slightly in error, and their errors will be larger as their resolving lengths are shortened. We show how to determine whether a given set G of measured gross Earth data permits such a construction of localized averages, and, if so, how to find the shortest length scale over which G gives a local average structure at a particular depth if the variance of the error in computing that local average from G is to be less than a specified amount. We apply the general theory to the linear problem of finding the depth variation of a frequency-independent local elastic dissipation (Q) from the observed damping rates of a finite number of normal modes. We also apply the theory to the nonlinear problem of finding density against depth from the total mass, moment and normal-mode frequencies, in case the compressional and shear velocities are known.
OBJECTIVE: To review existing methods and illustrate the use of a new, simple method for identifying inaccurate reports of dietary energy intake (rEI). DESIGN: Comparison of rEI with energy requirements estimated by using total energy expenditure predicted (pTEE) from age, weight, height and sex using a previously published equation. Propagation of error calculations was performed and cut-offs for excluding rEI at plus or minus two standard deviations (+/-2 SD) and +/-1 SD for the agreement between rEI and pTEE were established. SETTING: Dietary survey in a US national cohort: the Continuing Survey of Food Intakes by Individuals (CSFII), 1994-96. SUBJECTS: Men and non-pregnant, non-lactating women aged 21-45 years in the CSFII who provided two multiple-pass 24-hour recalls, height and weight (n = 3755). RESULTS: Average rEI was 77% of pTEE in men, and 64% of pTEE in women. Calculated cut-offs were rEI <40% or >160% of pTEE (+/-2 SD) and <70% or >130% of pTEE (+/-1 SD), respectively. Use of only the +/-1 SD cut-offs, not the +/-2 SD cut-offs, resulted in a relationship between rEI and body weight similar to what was expected (based on an independently calculated relationship between rEI and measured TEE). Exclusion of rEI outside either the +/-2 SD (11% of subjects) or +/-1 SD (57% of subjects) cut-offs did not affect mean reported macronutrient intakes, but did markedly affect relationships between dietary composition and body mass index. CONCLUSIONS: When examining relationships between diet and health, use of +/-1 SD cut-offs may be preferable to +/-2 SD cut-offs for excluding inaccurate dietary reports.
BACKGROUND: Multiple reaction monitoring mass spectrometry (MRM-MS) of peptides with stable isotope-labeled internal standards (SISs) is increasingly being used to develop quantitative assays for proteins in complex biological matrices. These assays can be highly precise and quantitative, but the frequent occurrence of interferences requires that MRM-MS data be manually reviewed, a time-intensive process subject to human error. We developed an algorithm that identifies inaccurate transition data based on the presence of interfering signal or inconsistent recovery among replicate samples. METHODS: The algorithm objectively evaluates MRM-MS data with 2 orthogonal approaches. First, it compares the relative product ion intensities of the analyte peptide to those of the SIS peptide and uses a t-test to determine if they are significantly different. A CV is then calculated from the ratio of the analyte peak area to the SIS peak area from the sample replicates. RESULTS: The algorithm identified problematic transitions and achieved accuracies of 94%-100%, with a sensitivity and specificity of 83%-100% for correct identification of errant transitions. The algorithm was robust when challenged with multiple types of interferences and problematic transitions. CONCLUSIONS: This algorithm for automated detection of inaccurate and imprecise transitions (AuDIT) in MRM-MS data reduces the time required for manual and subjective inspection of data, improves the overall accuracy of data analysis, and is easily implemented into the standard data-analysis work flow. AuDIT currently works with results exported from MRM-MS data-processing software packages and may be implemented as an analysis tool within such software.
Intubation, which requires sedation and myorelaxants, may lead to inaccurate neurological evaluation of severely head-injured patients. Aims of this study were to describe the early clinical evolution of traumatic brain injured (TBI) patients admitted to intensive care unit (ICU), to identify cases of over-estimated neurological severity, and to quantify the risk factors for this over-estimation. A total of 753 TBI patients consecutively admitted to ICU of three academic neurosurgical hospitals (NSH) were assessed. Cases whose severity was potentially over-estimated were identified by four criteria and indicated as "mistakenly severe" (MS): (1) no surgical intracranial masses; (2) could not follow commands at neurological assessment; (3) were dismissed from the ICU in < or =3 days to a regular ward; and (4) had regained the ability to obey commands. A total of 675 patients were intubated and/or sedated-paralyzed at the post-stabilization evaluation. In all, 304 patients had surgically treated intracranial masses. Among the 449 non-surgical cases, 58 patients fulfilling the criteria for MS were identified. The main features distinguishing MS from truly severe cases were younger age, higher Glasgow Coma Scale (GCS) score at all time points, Marshall classification of Computerized Tomographic (CT) scan mostly Diffuse Injury I and II, fewer pupillary abnormalities, and a lower frequency of hypoxia, hypotension, and extra-cranial injuries. In a certain proportion of non-surgical TBI patients, mostly intubated and sedated, neurological examination is difficult and severity can be over-estimated. Risk factors for this inaccurate evaluation can be identified, and clinical decisions should be based on further examination.
In this paper, we propose a high-resolution image reconstruction algorithm considering inaccurate subpixel registration. A regularized iterative reconstruction algorithm is adopted to overcome the ill-posedness problem resulting from inaccurate subpixel registration. In particular, we use multichannel image reconstruction algorithms suitable for applications with multiframe environments. Since the registration error in each low-resolution image has a different pattern, the regularization parameters are determined adaptively for each channel. We propose two methods for estimating the regularization parameter automatically. The proposed algorithms are robust against registration error noise, and they do not require any prior information about the original image or the registration error process. Information needed to determine the regularization parameter and to reconstruct the image is updated at each iteration step based on the available partially reconstructed image. Experimental results indicate that the proposed algorithms outperform conventional approaches in terms of both objective measurements and visual evaluation.
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In response to lawyers' critiques of earlier staged-crime, mock-jury studies, 16 eyewitnesses to a staged crime were videotaped while being questioned by lawyers in a real courthouse. Accurate and inaccurate eyewitnesses were questioned by experienced or inexperienced lawyers for the prosecution and defense. Subsequently, 178 University of Alberta undergraduates served as mock-jurors and attempted to detect the accuracy of the witnesses based on their taped testimony. As in the previous research, the overall rate of belief was quite high (69%), and the subjects believed the testimony of accurate and inaccurate eyewitnesses at about the same rate (68% vs. 70%, respectively). Lawyers' experience failed to influence verdict. Confidence of the eyewitness was significantly related to belief of their testimony. The data replicate the previous findings and demonstrate that lack of expertise of the questioners does not account for the failure to detect eyewitness accuracy in this paradigm.
In this paper, a novel variational Bayesian (VB)-based adaptive Kalman filter (VBAKF) for linear Gaussian state-space models with inaccurate process and measurement noise covariance matrices is proposed. By choosing inverse Wishart priors, the state together with the predicted error and measurement noise covariance matrices are inferred based on the VB approach. Simulation results for a target tracking example illustrate that the proposed VBAKF has better robustness to resist the uncertainties of process and measurement noise covariance matrices than existing state-of-the-art filters.
Interdisciplinary approaches to identifying, understanding, and remediating people's reliance on inaccurate information that they should know to be wrong. Our lives revolve around the acquisition of information. Sometimes the information we acquire—from other people, from books, or from the media—is wrong. Studies show that people rely on such misinformation, sometimes even when they are aware that the information is inaccurate or invalid. And yet investigations of learning and knowledge acquisition largely ignore encounters with this sort of problematic material. This volume fills the gap, offering theoretical and empirical perspectives on the processing of misinformation and its consequences. The contributors, from cognitive science and education science, provide analyses that represent a variety of methodologies, theoretical orientations, and fields of expertise. The chapters describe the behavioral consequences of relying on misinformation and outline possible remediations; discuss the cognitive activities that underlie encounters with inaccuracies, investigating why reliance occurs so readily; present theoretical and philosophical considerations of the nature of inaccuracies; and offer formal, empirically driven frameworks that detail when and how inaccuracies will lead to comprehension difficulties. Contributors Peter Afflerbach, Patricia A. Alexander, Jessica J. Andrews, Peter Baggetta, Jason L. G. Braasch, Ivar Bråten, M. Anne Britt, Rainer Bromme, Luke A. Buckland, Clark A. Chinn, Byeong-Young Cho, Sidney K. D'Mello, Andrea A. diSessa, Ullrich K. H. Ecker, Arthur C. Graesser, Douglas J. Hacker, Brenda Hannon, Xiangen Hu, Maj-Britt Isberner, Koto Ishiwa, Matthew E. Jacovina, Panayiota Kendeou, Jong-Yun Kim, Stephan Lewandowsky, Elizabeth J. Marsh, Ruth Mayo, Keith K. Millis, Edward J. O'Brien, Herre van Oostendorp, José Otero, David N. Rapp, Tobias Richter, Ronald W. Rinehart, Yaacov Schul, Colleen M. Seifert, Marc Stadtler, Brent Steffens, Helge I. Strømsø, Briony Swire, Sharda Umanath
BACKGROUND: Modern navigation techniques allow precise positioning of the acetabular cup relative to the anterior pelvic plane. Variations in pelvic tilt will affect the resulting spatial orientation of the cup. METHODS: We measured pelvic tilt in 30 volunteers with an inclinometer combined with an ultrasonographic position measurement system. A mathematical algorithm was developed to calculate the resulting cup position measured on standard radiographs, depending on pelvic tilt. RESULTS: Average pelvic tilt at rest was -4 degrees in the lying position and -8 degrees in the standing position, and ranged from -27 degrees to +3 degrees. Pelvic reclination of 1 degree will lead to functional anteversion of the cup of approximately 0.7 degree. INTERPRETATION: Pelvic tilt makes navigation systems referring to the anterior plane inaccurate.