Treatment Integrity Failures during Timeout from Play.

The human interaction with machines has come a long way from the ancient times to the Artificial Intelligence (AI) tools today, threatening individuals and organisations in various professions. ChatGPT (CGPT) has entered on the scenes to replace researchers and research assistants, creating a hysertia and hype at every level that CGPT will replace science. Although it is dubbed as a substitute of scholars, CGPT, its true implications can be judged by the error of omission versus commission to answer whether CGPT plays an effective role in the efficiency and effectiveness of supporting research and practice. Based on the framework of errors of commission and omission, this article tests the function of CGPT as a research assistant, which answers theoretical question why biases occur (if any) and how they occur, and a practical question how to prevent them. This article is based on an experiment with CGPT to test whether it can produce (a) summaries based on citations, (b) citations based on summaries it produced, and (c) citations based on the published abstract of the research article in the literature. For consistency, this study uses 1 author (who was able and willing to participate), 34 publications in referred journals, multiple experiments. The result shows three patterns. First, CGPT produced summaries of all citations correctly, and the proximity between the abstract and summary ranged from 5 to 10 with average about 7 on 10-scale. Second, the summary to citation was 100% inaccurate and biased. Third, the link from the abstract to citation was 100% biased. In the theory of errors of omission and errors of commission, this study explains where, how and why those errors occur in the contextualised world.

We assess the surface gravity data requirements for a 5-mm quasi-geoid model for the Netherlands mainland and continental shelf in terms of omission and commission errors. The omission error critically depends on the roughness of the topography and bathymetry. For the Netherlands continental shelf, Central and Northern Netherlands, the omission error is well described by the model 0.32d mm, where d is the data spacing in km. For the more hilly Southern Netherlands, the omission error model is 0.92d mm. The commission error depends on the kernel modification, the data spacing, and the data accuracy. When using the spheroidal Stokes kernel, it is well described by 0.277 d σΔg mm, where σΔg is the noise standard deviation of surface gravity data in mGal. An upper bound of the commission error of the state-of-the-art satellite-only gravity model GOCO05S over the Netherlands is e0.03676L–11.419 mm, where L is the maximum degree up to which this model is used. Only if this model is truncated at a sufficiently low degree, e.g., at degree 100, its contribution to the total commission error can be neglected. We determine the total error as the sum of commission and omission errors. Hence, to realize a 5-mm quasi-geoid model for the Netherlands mainland and continental shelf, a data spacing of 3.5 km is needed when assuming a noise standard deviation of 1.5 mGal for surface gravity data. The currently available land-based gravity data fulfill this requirement. This does not apply to the situation at sea, where the density of the shipboard gravity data and the accuracy of the radar altimeter-derived data do not allow the realization of a 5-mm quasi-geoid model.

In this paper, the optimal threshold for fire detection is derived based on the probability density functions of the fire and background pixels. The threshold values and the commission and omission errors are computed according to several detection criteria: maximum likelihood, null-hypothesis testing, and minimum cost. This statistical approach enables the determination of optimal threshold value according to the specific requirements of the detection tasks I. INTRODUCTION Active fire detection using satellite thermal sensors usually involves thresholding the detected brightness temperature in several bands. The frequently used features for fire detection are the brightness temperature in the 4-µm wavelength band (T4) and the brightness temperature difference between the 4- µm and 11- µm bands (∆T=T4-T11) (1), (2), (3). Due to the statistical nature of the fire and background temperature distribution, no matter how the thresholds are chosen, there are bound to be commission errors (i.e. false alarms) and omission errors (false negatives) in the detection outcomes. In the commonly used fire detection algorithms, the thresholds are often arbitrarily defined, and hence may not be optimal for a given fire detection task. The optimal threshold values are expected to be site dependent. They are different in different regions and for different fire conditions (such as smoldering and flaming fires). Hence, a global set of threshold values may not work optimally for a specific site. The task of active fire hot spot detection can be modeled as a stochastic target detection procedure (4). In this model, each pixel of the image occupies a point (T4, ∆T) in the two- dimensional feature space, and each pixel belongs to either the fire class or the non-fire background class. This approach considers the probability density functions of the fire and background pixels and optimal thresholds are derived depending on the specific objectives of the detection tasks. In a previous work (4), we implemented a method for deriving the optimal detection threshold by minimizing a cost function which is a weighted sum of the omission and commission errors. Alternatively, the threshold can also be derived based on other criteria. In this paper, we derive the optimal thresholds for detecting active fires in MODIS scenes using various detection criteria: maximum likelihood, constant false alarm rate, and null-hypothesis testing. The test data set consists of several MODIS scenes over Sumatra and Borneo islands and coincidental high resolution SPOT scenes (5). The SPOT data serves as ground truth for validation of MODIS hotspots detected by the new algorithms based on stochastic models. The probability density functions (pdf's) of the fire and background pixels are derived from this dataset and these pdf's are used to derive the optimal thresholds for active fire detection.

Association between DRD4 Gene and Performance of Children with ADHD in a Test of Sustained Attention

AimPresence‐only data represent a significant source of information for quantifying biodiversity distributions and provide opportunities for use in conservation planning. The large databases of presence‐only records that are available and the lower cost of acquisition could help overcome the traditional problem of lack of data for conservation. However, there are risks associated with the use of presence‐only data inherent with the lack of true absences that might cause omission errors (species are erroneously thought to be absent) and loss of efficiency (more areas are thought to be necessary than needed). These errors could constrain the economic viability of conservation plans and thus the success of conservation practice. We therefore evaluated the opportunities and risks of using presence‐only data for conservation planning.LocationNorthern Australia.MethodsThe effects of using two different types (presence‐only and presence–absence) and different quantities of data were simulated by building predictive models on different subsets of data with increasing numbers of presence–absence or presence‐only records or a combination of both, for 80 freshwater fish species. We then compared the performance of conservation planning outcomes with the best information attainable (a true model built on the complete set of presence–absence data). We measured omission and commission errors in conservation planning outcomes, and the efficiency of and return on the investment in data acquisition.ResultsIncluding presence‐only data helped reduce commission and omission errors in conservation planning outcomes, but only when used in combination with at least some presence–absence data. The use of just a large quantity of presence‐only data resulted in significant reductions in the efficiency of conservation planning outcomes, as more areas than actually needed were required to achieve conservation targets. This reduction in efficiency was mainly related to inflated omission errors.Main conclusionsWe recommend using presence‐only data cautiously if this is the only source of data available; whenever possible, presence‐only data should be complemented with presence–absence data.

This article develops and tests a model of how organizational structure influences organizational performance. Organizational structure, conceptualized as the decision‐making structure among a group of individuals, is shown to affect the number of initiatives pursued by organizations and the omission and commission errors (Type I and II errors, respectively) made by organizations. The empirical setting is more than 150,000 stock‐picking decisions made by 609 mutual funds. Mutual funds offer an ideal and rare setting to test the theory, since there are detailed records on the projects they face, the decisions they make, and the outcomes of these decisions. The study's independent variable, organizational structure, is coded based on fund management descriptions made by Morningstar, and estimates of the omission and commission errors are computed by a novel technique that uses bootstrapping to create measures that are comparable across funds. The findings suggest that organizational structure has relevant and predictable effects on a wide range of organizations. In particular, the article shows empirically that increasing the consensus threshold required by a committee in charge of selecting projects leads to more omission errors, fewer commission errors, and fewer approved projects. Applications include designing organizations that achieve a given mix of exploration and exploitation, as well as predicting the consequences of centralization and decentralization. This work constitutes the first large‐sample empirical test of the model by Sah and Stiglitz (). Copyright © 2012 John Wiley & Sons, Ltd.

Prescribing errors are one of the leading causes of diminished therapeutic outcomes even resulting in treatment failures. The Present study is a comparative evaluation of prescribing errors in non-steroidal antiinflammatory drugs containing prescriptions in four different health care facilities of District Khairpur, Sindh, Pakistan, since these drugs are among the widely-misused drugs. A total of 479 prescriptions, which were written in the primary health care facilities, public hospitals, university hospital and private hospitals were collected, compared and analyzed for common omission and commission prescribing errors as per prescription writing guidelines/parameters established by the World Health Organization, The drug information book and the British national formulary. Only 21 (4.4%) prescriptions consisting of 9 prescriptions of the university hospital and 12 prescriptions of the private hospitals were found error free and the rest 458 (95.6 %) prescriptions from different health care facilities contained different types of omission and commission errors. In omission errors, patient diagnosis, registration number of the prescriber and duration of therapy was missing in 84, 88.9 and 82.8 % prescriptions, respectively. Among commission errors, 85.2% of prescriptions were ambiguously written. A significant percentage of these errors were found in routine practice. As compared to all health care facilities, it was alarmingly found that, more number of prescribing errors were found in prescriptions of primary healthcare facilities followed by public hospitals followed by the university hospital and least number of prescribing errors were found in prescriptions of private hospitals. Computerized physician order entry and continuous educational training programs for prescribers to be executed in order to decrease these vital prescribing errors, besides that evaluation of prescriptions by pharmacists for prescribing errors can diminish the magnitude of these grave and life threatening errors.

Errors directly causing serious harm are rare during pediatric trauma resuscitation, limiting the use of adverse outcome analysis for performance improvement in this setting. Errors not causing harm because of mitigation or chance may have similar causation and are more frequent than those causing adverse outcomes. Analyzing these error types is an alternative to adverse outcome analysis. The purpose of this study was to identify errors of any type during pediatric trauma resuscitation and evaluate team responses to their occurrence. Errors identified using video analysis were classified as errors of omission or commission and selection errors using input from trauma experts. The responses to error types and error frequency based on patient and event features were compared. Thirty-nine resuscitations were reviewed, identifying 337 errors (range, 2-26 per resuscitation). The most common errors were related to cervical spine stabilization (n = 93, 27.6%). Errors of omission (n = 135) and commission (n = 106) were more common than errors of selection (n = 96). Although 35.9% of all errors were acknowledged and compensation occurred after 43.6%, no response (acknowledgement or compensation) was observed after 51.3% of errors. Errors of omission and commission were more often acknowledged (40.7% and 39.6% vs. 25.0%, p = 0.03 and p = 0.04, respectively) and compensated for (50.4% and 47.2% vs. 29.2%, p = 0.004 and p = 0.01, respectively) than selection errors. Response differences between errors of omission and commission were not observed. The number of errors and the number of high-risk errors that occurred did not differ based on patient or event features. Errors are common during pediatric trauma resuscitation. Teams did not respond to most errors, although differences in team response were observed between error types. Determining causation of errors may be an approach for identifying latent safety threats contributing to adverse outcomes during pediatric trauma resuscitation. Therapeutic study, level III.

Background. Communication errors are a source of preventable medical errors. In high-risk health care settings, identifying the source and addressing root causes can reduce error and improve patient safety. While air medical transport is a high-risk setting, its sources and rates of error have been investigated only within the last several years. Objectives. This investigation examined the rate and types of communication errors during call booking of interfacility air medical transports. The primary objective was to determine the incidence and type of errors when the initial requests for transfer took place between the sending facility and transport medicine communication center. The secondary objective was to identify potential underlying causes of these errors. Methods. Requests for urgent and emergent interfacility air medical transfers were examined prospectively during a consecutive two-week period. As the first step in call booking, sending facility staff speak directly to communication center staff and are asked for administrative, demographic, and medical details to determine patient acuity and call priority. After this information was captured, investigators contacted the sending facility to verify the information and identify any communication errors. Errors were classified as major (potentially impacting care) or minor (unlikely to impact care) and as errors of omission or commission. Common error types were presented to a management focus group to identify potential contributing causes for these errors. Results. One hundred twelve calls were randomly selected during the study period, with 98 meeting study criteria. Of those, 41 (42%%) calls contained a total of 65 errors. Eleven were classified as major, including five errors of omission and six errors of commission. The most common major errors were recording “no drug allergies” when a drug allergy was present (n == 4), incorrect diagnosis (n == 2), and failure to record that patients were intubated or required mechanical ventilation (n == 2 each). There were 54 minor errors, including 41 omission errors and 13 commission errors. Nearly half the errors were attributed to procedures and software. No identified error resulted in patient harm or an adverse outcome. Conclusions. Communication-based errors are common in the initial phases of call booking in air medical transport. Human and process-driven errors contribute equally to these errors. Key words: communication; error; air ambulance; dispatch; safety

In a paper in this issue (Beresford et al., 2011), we set out to quantify the extent to which site-based conservation initiatives overlapped with the ranges of globally threatened bird species in Africa, using a GIS approach. We considered Protected Areas and Important Bird Areas (IBAs), both of which cover c. 7% of the land surface of Africa. The former, as noted by both Brooks & Matiku (2011) and Rodrigues (2011), carry significant governmental weight despite not necessarily being identified for their conservation value, while the latter (which are of conservation value to other taxa in addition to birds –Pain et al., 2005) have no legal standing, but are identified using objective criteria that include their value for globally threatened species (Fishpool & Evans, 2001). We find that Protected Areas perform poorly at protecting the ranges of Africa's most threatened birds, covering just 13.9% on average, and even where a Protected Area overlaps part of an IBA, the part excluded from the Protected Area has higher value for these species than the protected part. As Rodrigues (2011) notes, the limitations of GIS studies that utilize Extent of Occurrence (EOO) maps are well documented. We therefore attempted to reduce the commission errors inherent in the use of EOO maps by analysing extent of suitable habitat (ESH: the area of potentially suitable vegetation types within the altitudinal preferences of the species (Rondinini, Stuart & Boitani, 2005; Buchanan et al., 2008)). While it is desirable to move beyond interpolation approaches based on EOO or ESH and utilize only presence/absence data derived from recent complete field surveys, these are not available for the majority of species. Even in the most well-watched countries, such as the United Kingdom, the most reliable information on the distribution of birds comes from systematic atlas surveys in which ranges are interpolated from sampled field counts which themselves record only a tiny proportion of the individuals present. At least for the foreseeable future therefore, we will have to continue to assess geographical distributions using interpolative approaches, whilst acknowledging the limitations of these methods. ESH estimates were considerably smaller than EOOs for most species, with a concomitant reduction in commission errors and increase in omission errors. Reducing commission errors reduces the likelihood that a species is assumed to be conserved elsewhere (Rodrigues & Gaston, 2001), and hence in our study, the danger of overestimating the coverage of species' ranges by Protected Areas or IBAs. Omission errors, on the other hand, reduce the estimated overlap between sites and species' ranges. Considering the information we presented, Rodrigues (2011) suggests that the ESH approach was not well able to distinguish between occupied and unoccupied areas of the EOO, because both approaches have similar ratios of true presences to total predicted presences. We agree that by focusing on other aspects of the analysis and by presenting only a broad overview of the accuracy of the ESH approach compared with EOOs (table 1; Beresford et al., 2011), we did not show the full advantage of the ESH method. A species-level analysis indicates that although the ESH comprises, on average, 28% of the EOO – hence reducing the chance of the species being assigned to areas where it did not occur – this did not make any difference to the accuracy of the estimated distribution for 74 species [47%, assessed by comparing the total numbers of errors (commission plus omission) using ESH vs. EOO]. Importantly, however, it did improve accuracy for 58 species (37%), decreasing commission errors by, on average, 11.8 IBAs per species. This was at the expense of a reduction in the accuracy of maps for 25 species, due to an increase in omission errors, although these averaged just 1.8 sites per species (Fig. 1). Increases in omission errors versus decreases in commission errors observed when using ESH instead of EOO. Each point represents one species. For all species falling on the right of the line, the ESH reduced commission errors more than it introduced omissions. ESH, extent of suitable habitat; EOO, Extent of Occurrence. While considerable inaccuracies remain, especially in commission errors (table 1; Beresford et al., 2011), we suggest that the increase in accuracy for over a third of species, with no effect on almost half of the species, justifies the approach. It is also important to note that commission errors are likely to be overestimated in our analysis, as the data used only recorded species present in sufficient abundance to trigger IBA designation of sites (Fishpool & Evans, 2001), rather than being true presence/absence data based on complete surveys. We do however share the concerns of Rodrigues about the weaknesses of range maps. Even systematic atlases are estimates of broad-scale distributions based on small amounts of field data, and the accuracy of them will depend on the size of sampling units (Gibbons et al., 2007). Therefore, we emphasize that EOO or ESH methods are not a substitute for dedicated, site-based field-collected data. Until such complete field survey data are available (perhaps guided partially, but not exclusively, by ESH), we think that ESH remains useful as long as its limitations are acknowledged. Brooks & Matiku (2011) suggest that the ESH approach could be used to inform planning policies and to guide research priorities for environmental assessments to minimize the impact of developments. This could in turn lead to targeted field surveys which would, over time, increase our knowledge of species' distributions and reduce our reliance on broad EOO maps or GIS-based estimates of ranges such as ESH. While it is important to consider the methods used to assess species ranges, we believe that any errors in the range maps are likely to have affected the analysis for Protected Areas and IBAs in the same manner. The substantial differences in coverage between the two site networks and between species of differing conservation status should not be taken as absolute values, due to these uncertainties in the range maps, but the direction and approximate magnitude of the differences are likely to be robust. These results indicate that the Protected Area network needs considerable targeted expansion to improve coverage of globally threatened species. As Brooks & Matiku (2011) point out, expansion of the Protected Area network should be targeted to the areas of highest importance, and we hope that our paper is used to support arguments for the expansion to cover sites of objectively assessed, recognized importance (such as IBAs and other key biodiversity areas). While the Protected Area network may be the most effective strategy for protecting tropical biodiversity (Brooks, Wright & Sheil, 2009), Protected Areas may not be the most or sole appropriate conservation action for all species. Many species have extensive ranges, occur at low densities and/or cannot be adequately protected by site-based conservation, and may therefore require alternative or additional approaches (Boyd et al., 2008). In other cases, community-based management, rather than formal designation, may be the most appropriate means of ensuring protection, for example, for eight of the nine most threatened unprotected IBAs in Uganda (BirdLife International, 2008). There is increasing evidence that legal protection is effective at reducing, though not necessarily halting, land cover change (e.g. Leverington et al., 2010). Consequently, monitoring is required not just of the total area of land or sea designated as protected, but also of the effectiveness of these designations at reducing biodiversity loss. Such monitoring will be a key area of development for the interface between pure and practical conservation. We would like to thank Tom Brooks, Paul Matiku and Ana Rodrigues for their comments. We appreciate the opportunity to clarify our findings, and to discuss our results in a broader context.

This paper presents an accuracy assessment of the main global scale Burned Area (BA) products, derived from daily images of the Moderate-Resolution Imaging Spectroradiometer (MODIS) Fire_CCI 5.1 and MCD64A1 C6, as well as the previous versions of both products (Fire_CCI 4.1 and MCD45A1 C5). The exercise was conducted on the boreal region of Alaska during the period 2000–2017. All the BA polygons registered by the Alaska Fire Service were used as reference data. Both new versions doubled the annual BA estimate compared to the previous versions (66% for Fire_CCI 5.1 versus 35% for v4.1, and 63% for MCD64A1 C6 versus 28% for C5), reducing the omission error (OE) by almost one half (39% versus 67% for Fire_CCI and 48% versus 74% for MCD) and slightly increasing the commission error (CE) (7.5% versus 7% for Fire_CCI and 18% versus 7% for MCD). The Fire_CCI 5.1 product (CE = 7.5%, OE = 39%) presented the best results in terms of positional accuracy with respect to MCD64A1 C6 (CE = 18%, OE = 48%). These results suggest that Fire_CCI 5.1 could be suitable for those users who employ BA standard products in geoinformatics analysis techniques for wildfire management, especially in Boreal regions. The Pareto boundary analysis, performed on an annual basis, showed that there is still a potential theoretical capacity to improve the MODIS sensor-based BA algorithms.

Bimodal response sensitivity and bias in a test of sustained attention contrasting patients with schizophrenia and bipolar disorder to normal comparison group

In an article, Infant mortality trends in the Soviet Union, published last year in this journall Ellen Jones and Fred W. Grupp argue that the officially reported increase in infant mortality rates in the Soviet Union in the early 1970s is largely attributable to improvements in the vital registry system in the USSR's southern tier republics. They present this interpretation and supporting evidence as a refutation of the findings of a report by Christopher Davis and myself that the increase was real and significant.2 Errors of omission and of commission in the article by Jones and Grupp call into question the validity of their argument. To start with an error of both omission and commission, the authors fail to make reference to the work of M. S. Bednyy, M.D., head, since 1979, of an innovative research unit on medical demography formed by the Ministry of Health of the Russian Republic, and extensively cited in the Davis/Feshbach report.3 Bednyy cites numerous reasons for the real increase in infant mortality in the Soviet Union in the 1970s-including an increase in the number of children with congenital anomolies and in the proportions of children born prematurely; and a lack of correlation of the growth in the numbers of doctors and hospital beds with health indicators. Moreover he provides abundant evidence of increases in mortality at all ages. The extensiveness of underreporting in the 1950s and 1960s-let alone in the 1930s, which could have had nothing to do with the alleged increase in the 1970s-can be disputed by reference to the very evidence that Jones and Grupp themselves provide. (I do not take issue with their evidence from ethnographer Kozlov; however, Eberstadt's response [see below] to the Jones and Grupp article provides information from an interview with Kozlov, which modifies the strength of Kozlov's very brief assertion concerning underreporting in the Central Asian republics in the 1970s.) Take, for example, the

Psycholinguistic research over the past decade has suggested that children's linguistic knowledge includes dedicated representations for frequently‐encountered multiword sequences. Important evidence for this comes from studies of children's production: it has been repeatedly demonstrated that children's rate of speech errors is greater for word sequences that are infrequent and thus unfamiliar to them than for those that are frequent. In this study, we investigate whether children's knowledge of multiword sequences can explain a phenomenon that has long represented a key theoretical fault line in the study of language development: errors of subject‐auxiliary non‐inversion in question production (e.g., “why we can't go outside?*”). In doing so we consider a type of error that has been ignored in discussion of multiword sequences to date. Previous work has focused on errors of omission – an absence of accurate productions for infrequent phrases. However, if children make use of dedicated representations for frequent sequences of words in their productions, we might also expect to see errors of commission – the appearance of frequent phrases in children's speech even when such phrases are not appropriate. Through a series of corpus analyses, we provide the first evidence that the global input frequency of multiword sequences (e.g., “she is going” as it appears in declarative utterances) is a valuable predictor of their errorful appearance (e.g., the uninverted question “what she is going to do?*”) in naturalistic speech. This finding, we argue, constitutes powerful evidence that multiword sequences can be represented as linguistic units in their own right.

Despite the persistence of attention deficit hyperactivity disorder (ADHD) into adulthood and adolescence, there are few objective, reliable instruments (based on patient performance) that have been shown to be able to predict current and retrospective ADHD symptoms. The present study aimed to explore whether a validated VR test called Nesplora Aquarium is able to predict ADHD symptoms in adults and adolescents, based on both current and retrospective self-reports. A non-clinical sample of 156 adults and adolescents (70 women and 86 men) between 16 and 54 years of age (M = 21.23, SD = 8.04) took part in the study. Virtual reality (VR) variables such as the number of correct answers, omission and commission errors, among others, were used to predict current and retrospective self-reported symptoms of ADHD using multiple regression models. Correct answers and omission errors in the VR test significantly predicted both current and retrospective ADHD symptoms. However, only the number of perseveration errors and gender were able to significantly predict retrospective ADHD symptoms. These findings suggest that inattention problems tend to remain after adolescence, while perseveration errors (which have been related to impulsive behavior) and gender differences tend to diminish.