Significant Systematic Errors Research Articles

Tidal heating as a discriminator for horizons in equatorial eccentric extreme mass ratio inspirals

Tidal heating in a binary black hole system is driven by the absorption of energy and angular momentum by the black hole’s horizon. Previous works have shown that this phenomenon becomes particularly significant during the late stages of an extreme mass ratio inspiral (EMRI) into a rapidly spinning massive black hole, a key focus for future low-frequency gravitational-wave observations by (for instance) the Laser Interferometer Space Antenna mission. Past analyses have largely focused on quasicircular inspiral geometry, with some of the most detailed studies looking at equatorial cases. Though useful for illustrating the physical principles, this limit is not very realistic astrophysically, since the population of EMRI events is expected to arise from compact objects scattered onto relativistic orbits in galactic centers through many-body events. In this work, we extend those results by studying the importance of tidal heating in equatorial EMRIs with generic eccentricities. Our results suggest that accurate modeling of tidal heating is crucial to prevent significant dephasing and systematic errors in EMRI parameter estimation. We examine a phenomenological model for EMRIs around exotic compact objects by parametrizing deviations from the black hole (BH) picture in terms of the fraction of radiation absorbed compared to the BH case. Based on a mismatch calculation, we find that reflectivities as small as |R|2∼O(10−5) are distinguishable from the BH case, irrespective of the value of the eccentricity. We stress, however, that this finding should be corroborated by future parameter estimation studies. Published by the American Physical Society 2024

Modelling of cup anemometry and dynamic overspeeding in average wind speed measurements

Abstract. Cup anemometers measure average wind speed in the atmosphere and have been used for one and a half centuries by meteorologists. Within the last half century, cup anemometers have been used extensively in wind energy to measure wind resources and performance of wind turbines. Meteorologists researched cup anemometer behaviour and found dynamic overspeeding to be an inherent and significant systematic error. The wind energy community has strong accuracy requirements for power performance measurements on wind turbines, and this led in the last 2 decades to new research on cup anemometer characteristics, which was taken to a new level with the development of improved calibration procedures, cup anemometer calculation models and classification methods. Research projects in wind energy demonstrated, by field and wind tunnel measurements, that angular response was a significant contributor to uncertainty and that dynamic overspeeding was a significant but less important contributor. Earlier research was mainly made on cup anemometers with hemispherical cups on long arms, ​​​​​​​and dynamic overspeeding was considered an inherent and high uncertainty error for cup anemometers. Research on conical cups on short arms has now shown that zero or low overspeeding is present on a well-designed cup anemometer, providing a much lower overspeeding uncertainty error. Different cup anemometer calculation models were investigated in order to find derived overspeeding characteristics. The general and often used parabolic torque coefficient model showed that zero overspeeding is present when the speed ratio roots of the torque coefficient curve go through the equilibrium speed ratio and zero. The two-cup drag model is a special case of the parabolic torque coefficient model but with the second root being reciprocal to the equilibrium speed ratio. The drag model always results in a positive maximum overspeeding of the order of 1.1 times the turbulence intensity squared. A linear torque coefficient results in maximum overspeeding levels equal to the turbulence intensity squared. Torque characteristics of a cup anemometer with hemispherical cups fit slightly well to the drag model, but a cup anemometer with conical cups does not fit to the drag model nor the parabolic model; it fits better to a partial linear model and even better to an optimized torque model. The most accurate modelling of cup anemometer characteristics is at present made with the ACCUWIND model (Dahlberg et al., 2006). This model uses tabulated torque coefficient and angular response data measured in a wind tunnel. The ACCUWIND model is found in International Electrotechnical Commission (IEC) wind turbine power performance standards, where it is used in a classification system for estimation of operational uncertainties. For an actual comparison of two cup anemometers, with respectively hemispherical and conical cups, the influence of dynamic overspeeding was found to be relatively low compared to angular response, but for conical cups it was specifically low.

Accurate estimates of dynamical statistics using memory.

Many chemical reactions and molecular processes occur on time scales that are significantly longer than those accessible by direct simulations. One successful approach to estimating dynamical statistics for such processes is to use many short time series of observations of the system to construct a Markov state model, which approximates the dynamics of the system as memoryless transitions between a set of discrete states. The dynamical Galerkin approximation (DGA) is a closely related framework for estimating dynamical statistics, such as committors and mean first passage times, by approximating solutions to their equations with a projection onto a basis. Because the projected dynamics are generally not memoryless, the Markov approximation can result in significant systematic errors. Inspired by quasi-Markov state models, which employ the generalized master equation to encode memory resulting from the projection, we reformulate DGA to account for memory and analyze its performance on two systems: a two-dimensional triple well and the AIB9 peptide. We demonstrate that our method is robust to the choice of basis and can decrease the time series length required to obtain accurate kinetics by an order of magnitude.

A Novel X-ray Diffraction Procedure for Determining Residual Stresses Around Cold Expanded Holes

The continued interest in developing more accurate finite element models of the cold expansion process has driven the need for better measurement methodologies. This work details an x-ray diffraction (XRD) procedure explicitly designed to determine the residual stresses around a cold expanded hole. Aluminum coupons from two different alloys (2024-T351 and 7075-T651), with nominally 12-mm-diameter holes, were cold expanded to two different levels of applied expansion and measured using XRD. The results of a limited interlaboratory study highlight the reproducibility that one may expect to achieve by its application. For the majority of data points, the residual stresses characterized at each of the two laboratories were in agreement within the bounds of the residual stress determination experimental uncertainties, which were generally ± 15 MPa or less. After examining the differences between results obtained at each laboratory as a function of radial distance from the hole, it was found that no significant systematic error exists between data sets. Thus, the proposed novel procedure appears to provide a more precise and accurate determination of the residual stresses around cold expanded holes with a significant reduction in measurement uncertainty compared to conventional XRD measurement procedures. The results obtained using this novel procedure will be useful in calibrating new computational material models of the expansion process.

A critical review and meta-analysis of xenon-on-carbon sputter yield data

A systematic review and meta-analysis of sputter yield data for xenon ions normally incident on graphite at energies below 2000 eV was undertaken to identify systematic errors, determine the best model parameter values to represent yield as a function of energy, quantify uncertainty, and determine if the data support differences in yields for different types of graphite. A critical examination of the 11 published data sets for high density graphite, pyrolytic graphite, and amorphous carbon showed that, in general, they were carefully controlled to minimize errors. The most significant quantifiable systematic errors were those caused by the neglect of doubly charged ions, chemical erosion, and the impact of secondary electron emission on ion flux measurements. The effects of gas uptake and outgassing on mass loss measurements and unrepresentative surface textures may have biased other experiments, but these effects could not be quantified. The semi-empirical Eckstein model for yield as a function of energy was fit to data for the three graphite types using a hierarchical Bayesian statistical model, producing recommended fit parameters and probability distributions representing uncertainty in yields. The results showed that differences in yield for high density graphite and pyrolytic graphite were not statistically significant. Apparent differences in yield for amorphous carbon disappeared when the single data set available for energies below 150 eV was corrected for reasonable values of double ion content. Recommended procedures to avoid systematic errors and additional experiments and modeling to fill in gaps in our understanding are included.

High-dimensional inference of radio interferometer beam patterns I: parametric model of the HERA beams

ABSTRACT Accurate modelling of the primary beam is an important but difficult task in radio astronomy. For high dynamic range problems such as 21 cm intensity mapping, small modelling errors in the sidelobes, and spectral structure of the beams can translate into significant systematic errors. Realistic beams exhibit complex spatial and spectral structure, presenting a major challenge for beam measurement and calibration methods. In this paper series, we present a Bayesian framework to infer per-element beam patterns from the interferometric visibilities for large arrays with complex beam structure, assuming a particular (but potentially uncertain) sky model and calibration solution. In this first paper, we develop a compact basis for the beam so that the Bayesian computation is tractable with high-dimensional sampling methods. We use the Hydrogen Epoch of Reionization Array (HERA) as an example, verifying that the basis is capable of describing its single-element E-field beam (i.e. without considering array effects like mutual coupling) with a relatively small number of coefficients. We find that 32 coefficients per feed, incident polarization, and frequency, are sufficient to give percent-level and $\sim$10 per cent errors in the mainlobe and sidelobes, respectively, for the current HERA Vivaldi feeds, improving to $\sim 0.1{{\ \rm per\ cent}}$ and $\sim 1{{\ \rm per\ cent}}$ for 128 coefficients.

The Number of Microbubbles Generated During Cardiopulmonary Bypass Can Be Estimated Using Machine Learning From Suction Flow Rate, Venous Reservoir Level, Perfusion Flow Rate, Hematocrit Level, and Blood Temperature.

Microbubbles (MBs) are known to occur within the circuits of cardiopulmonary bypass (CPB) systems, and higher-order dysfunction after cardiac surgery may be caused by MBs as well as atheroma dispersal associated with cannula insertion. As complete MB elimination is not possible, monitoring MB count rates is critical. We propose an online detection system with a neural network-based model to estimate MB count rate using five parameters: suction flow rate, venous reservoir level, perfusion flow rate, hematocrit level, and blood temperature. Perfusion experiments were performed using an actual CPB circuit, and MB count rates were measured using the five varying parameters. Bland-Altman analysis indicated a high estimation accuracy (R2 > 0.95, p < 0.001) with no significant systematic error. In clinical practice, although the inclusion of clinical procedures slightly decreased the estimation accuracy, a high coefficient of determination for 30 clinical cases (R2 = 0.8576) was achieved between measured and estimated MB count rates. Our results highlight the potential of this system to improve patient outcomes and reduce MB-associated complication risk.

Interval estimates of total content of antioxidants for different analytical assays

Determination of total content (сΣ) of similar analytes recalculated to the standard substance Xst is a commonly used but metrologically incorrect measuring procedure leading to significant systematic errors (B-type uncertainties). Interval estimate сΣ is an alternative method (V.I. Vershinin et al., 2016) not requiring recalculation to Xst and, in difference from calculating total indices, not depending on the nature and ratio of the sought group constituents present in the sample. Such estimates are used for evaluating total content of antioxidants (AO) in foodstuffs. However, the dependence of these estimates on the choice of group reagent and signal measuring procedure is uncertain. To address this question, model mixtures of AO with known сΣ values ranging from 10–5 to 10–4 mol/L were prepared and examined. Generalized signals were measured spectrophotometrically using Folin-Ciocalteu (F-C) and FRAP methods, and traditional and interval estimates of сΣ were calculated and compared. The true values of сΣ were within the respective intervals for all model mixtures; in case of F-C method the intervals were wider and shifted towards higher сΣ values. The FRAP procedure was modified by using AO-concentrations in mol-eq/L, reducing the reaction time and substituting the auxiliary reagent. This modification successfully leveled the sensibility coefficients of individual AOs and made the relative width of intervals three times as narrower. Modified FRAP method was used for group analysis of wines, black tea infusions and juices. Corresponding interval estimates of сΣ were obtained and compared. Unresolved issues and future research directions related to interval estimates are discussed.

Clinical reliability and validity of a video-based markerless gait evaluation method.

To explore the reliability and validity of gait parameters obtained from gait assessment system software employing a human posture estimation algorithm based on markerless videos of children walking in clinical practice. Eighteen typical developmental (TD) children and ten children with developmental dysplasia of the hip (DDH) were recruited to walk along a designated sidewalk at a comfortable walking speed. A 3-dimensional gait analysis (3D GA) and a 2-dimensional markerless (2D ML) gait evaluation system were used to extract the gait kinematics parameters twice at an interval of 2 h. The two measurements of the children's kinematic gait parameters revealed no significant differences (P > 0.05). Intra-class correlation coefficients (ICC) were generally high (ICC >0.7), showing moderate to good relative reliability. The standard error of measurement (SEM) values of all gait parameters measured by the two walks were 1.26°-2.91°. The system software had good to excellent validity compared to the 3D GA, with ICC values between 0.835 and 0.957 and SEM values of 0.87°-1.71° for the gait parameters measured by both methods. The Bland-Altman plot analysis indicated no significant systematic errors. The feasibility of the markerless gait assessment method using the human posture estimation-based algorithm may provide reliable and valid gait analysis results for practical clinical applications.

Error investigation for SI traceable pitch calibration of one-dimensional grating by grazing-incidence small-angle X-ray scattering

Grazing-incidence small-angle X-ray scattering (GI-SAXS) is a promising technique for investigating nanostructured surfaces, particularly for the fine pitch calibration of one-dimensional gratings. However, only a few studies validated this technique from a metrological perspective. In this study, we developed a GI-SAXS system traceable to length and angle standards and used it to analyze the uncertainty of pitch calibrations in detail. Consequently, we found statistically significant systematic errors which have not been reported so far. We also found that the systematic error varied depending on the signal width of the diffracted X-rays. Through theoretical modeling and quantitative experiments, we successfully explained that the source of the systematic error is intensity modulation along the grating truncation rod. Since the systematic error decreases with smaller signal width, optimizing the optical system may efficiently reduce the uncertainty.

J-PLUS: Photometric Recalibration with the Stellar Color Regression Method and an Improved Gaia XP Synthetic Photometry Method

We employ the corrected Gaia Early Data Release 3 photometric data and spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR7 to assemble a sample of approximately 0.25 million FGK dwarf photometric standard stars for the 12 J-PLUS filters using the stellar color regression (SCR) method. We then independently validate the J-PLUS DR3 photometry and uncover significant systematic errors: up to 15 mmag in the results from the stellar locus method and up to 10 mmag primarily caused by magnitude-, color-, and extinction-dependent errors of the Gaia XP spectra as revealed by the Gaia BP/RP (XP) synthetic photometry (XPSP) method. We have also further developed the XPSP method using the corrected Gaia XP spectra by B. Huang et al. and applied it to the J-PLUS DR3 photometry. This resulted in an agreement of 1–5 mmag with the SCR method and a twofold improvement in the J-PLUS zero-point precision. Finally, the zero-point calibration for around 91% of the tiles within the LAMOST observation footprint is determined through the SCR method, with the remaining approximately 9% of the tiles outside this footprint relying on the improved XPSP method. The recalibrated J-PLUS DR3 photometric data establish a solid data foundation for conducting research that depends on high-precision photometric calibration.

Evaluation of noise emissions of a ducted fan on a test rig

This paper presents an experimental research study on the sound excitation of a ducted fan designed for low-noise emissions. In particular, the influence of test rig vibrations as a significant systematic error when evaluating the noise emissions of ducted fans is discussed. A propulsor test rig was used to measure the sound emitted by a ducted fan. Significantly increased sound levels are ascertained at specific frequencies. The corresponding sources are often unexpectedly identified at the casing and structure of the rig using a sound source localization. By comparing sound pressures against vibrations, these sources are found to be excited by simultaneous test rig vibrations. When the rig vibrates, the sound pressure levels increase by up to 15 dB compared to vibration-free operation. The sound excitation caused by the rig vibrations predominates over the aerodynamically induced sound since the ducted fan itself emits little noise. In summary, these rig-dependent vibrations can lead to a considerable systematic measurement error for low-noise ducted fans. This error significantly complicates an accurate sound evaluation of such a ducted fan on an acoustic rig. Therefore, these results emphasize the importance of a vibration-free operating range and the necessity to quantify the sound excitation by rig-specific vibrations.

Enhanced precise orbit determination for GPS and BDS-2/3 with real LEO onboard and ground observations

Due to the current geographical situation in China that it is difficult to achieve globally well distributed ground monitoring stations for Chinese BeiDou Navigation System (BDS), the BDS Medium Earth Orbit (MEO) satellite orbital accuracy can be seriously affected by the insufficient length of continuous observation arc based on regional ground network. What is more, the highly static characteristics of BDS Geosynchronous Orbiting (GEO) satellites resulting in meter-level orbit determination accuracy is far from satisfactory for precise positioning services. In order to overcome these problems, the low Earth orbit (LEO) satellites serving as fast-moving space monitoring stations can be used as a good supplement for the current BDS ground monitoring stations layout. In this study, real measured spaceborne data from two LEO satellites, namely Fengyun-3D (FY-3D) and Tianjin University No. 1 (TJU-01), are collected and studied for the augmentation of BDS precise orbit determination (POD). The multipath errors of spaceborne code observations are comprehensively analyzed. It is found that not only BDS-2 relevant satellite-induced code bias but also near-field multipath errors, especially distinct in GPS, exist in a spaceborne environment. The piece-wise linear model is therefore established and applied to correct the code observations to reduce the multipath errors in the integrated POD processing. The GPS and BDS-2/3 POD solutions are compared with orbital overlapping differences and Satellite Laser Ranging (SLR) residuals validation. It is demonstrated that including the two LEO satellites can improve the orbit determination accuracy of GPS and BDS-2/3 significantly under a regional ground network, especially in the along component. The average overlapping orbital Root Mean Square (RMS) is decreased by 18.4 %, 34.3 %, 24.9 %, 21.4 %, and 7.8 % for the GPS, GEO, Inclined Geosynchronous Orbit (IGSO), BDS-2 MEO, and BDS-3 MEO satellites, respectively, in the along component. The RMS of SLR residuals is decreased from 37.1 cm to 17.8 cm for the GEO satellites, and the overall improvement is about 8 %-12 % for the BDS MEO satellites. There has also been a slight improvement under a global network, with an average improvement of 2–3 cm in the SLR residuals RMS. However, significant systematic errors are also observed in the SLR residuals in BDS GEO, IGSO, and MEO satellites, and are expected to be improved with refined observation models based on more LEO satellites, i.e., the phase center variation (PCV).

Evaluation of Uncertainties of Pressure Gain Measurements in Rotating Detonation Combustor

Experimentally measuring the pressure gain of a rotating detonation combustor through the method of equivalent available pressure is prone to many experimental uncertainties. A detailed analysis of sources of random and systematic uncertainties in the thrust and pressure gain is performed using data from a hydrogen/air-operated rotating detonation combustor. The combustor had an axial air inlet and a 50% exit constriction. The measured (negative) pressure gain values agree with the results in the literature for similar inlet-to-exit area ratios. The base drag correction on the centerbody was found to be the greatest source of uncertainty for the thrust. While thrust is the predominant source of random uncertainty in the pressure gain calculation, significant systematic errors can be committed due to the assumed exit Mach number. The impact of this assumption becomes more detrimental the closer to positive the measured pressure gain is. By experimentally evaluating the exit Mach number, the random and systematic uncertainty in pressure gain both decreased, indicating that this should be an essential step. A definitive demonstration of gain is challenging, given the assessed uncertainties, and recommendations are provided to increase the precision of the equivalent available pressure methodology.

Inferring nonlinear fractional diffusion processes from single trajectories

We present a method to infer the arbitrary space-dependent drift and diffusion of a nonlinear stochastic model driven by multiplicative fractional Gaussian noise from a single trajectory. Our method, fractional Onsager-Machlup optimisation (fOMo), introduces a maximum likelihood estimator by minimising a field-theoretic action which we construct from the observed time series. We successfully test fOMo for a wide range of Hurst exponents using artificial data with strong nonlinearities, and apply it to a data set of daily mean temperatures. We further highlight the significant systematic estimation errors when ignoring non-Markovianity, underlining the need for nonlinear fractional inference methods when studying real-world long-range (anti-)correlated systems.

Applicability Evaluation of Natural Gas State Equations at Low Temperatures

The paper analyzes the possibility of operating range expanding of natural gas state equations for low temperatures. The state equations of natural gas and methods of estimating the compressibility factor, entrenched in modern national and international standards, were analyzed. It has been shown that the range of their applicability is limited to a temperature value of 250 K, however, these temperature limitations is not restricted bystate equations directly butstipulated by the lack of reliable data about natural gas compressibility factor values at temperatures below 250 K and methods for complementary errorcalculation that may arise. The results of comparison of values of natural gas compressibility factor as a function of temperature at pressure of 1.3 and 6 MPa calculated by means of the most widely used state equations are presented. It was found that the results of the calculation according to the considered methods have satisfactory convergence within the range of 220 K, that generally confirms the applicability of modern state equations for low temperatures. In its turn, the effect of assumptions applied nowadays to definegas volume flow rateon flow metering error showed that application of substitutive compressibility values may result in significant complementary systematic error. This indicates the practicability of expanding the database of compressibility factor values for natural gas for low temperatures, as well as developmentof a standard to assess the value of the corresponding complementary error.

Sample plot design can affect the efficiency and accuracy of shrub coverage measurements in shrub-encroached grasslands

Shrub encroachment has become a global concern. The fraction of shrub coverage (FSC) is an important indicator that reflects the distribution of shrubs and the degree of shrub encroachment in grasslands. The line-point intercept (LPI) method is commonly used for FSC measurement in field surveys, but it’s often associated with issues of poor accuracy and low measurement efficiency. Here, we focus on Caragana microphylla shrub-encroached grassland as a case study. We used normalized difference vegetation index (NDVI) data obtained from unmanned aerial vehicle (UAV) to derive the actual values of FSC (FSCT) and to simulate measurements using the LPI method. We compared the results for measurements based on different sample plot designs, including variation in plot shape and line distribution, the number of sample lines, and the sample point spacings. The aim was to investigate the influence of these main parameters of sample plot design upon measurement results, in order to provide a reference for FSC measurements in field experiments. We first calculated FSCT and stratified the plots according to coverage levels. Based on this, we further evaluated the measurement accuracy of the LPI method under different parameter settings. The results revealed significant systematic errors in the measurement from circular plots. For square plots, the minimum number of lines required for the “high,” “medium,” and “low” coverage groups are 48, 16, and 8 (for 80% accuracy), and likewise, 108, 24, and 16 (for 90% accuracy), respectively. Futuremore, point spacings of 0.1 m and 0.5 m can achieve the same accuracy as the original spacing (0.02 m). We conclude that the systematic errors in circular plots are caused by the radial distribution of lines, whereas in square plots, achieving an efficient measurement requires considering different coverage levels, ensuring an adequate number of lines, and setting a relatively smaller point spacing.

Automated estimation of mitral annular plane systolic excursion by artificial intelligence from 3D ultrasound recordings

Perioperative monitoring of cardiac function is beneficial for early detection of cardiovascular complications. The standard of care for cardiac monitoring performed by trained cardiologists and anesthesiologists involves a manual and qualitative evaluation of ultrasound imaging, which is a time-demanding and resource-intensive process with intraobserver- and interobserver variability. In practice, such measures can only be performed a limited number of times during the intervention. To overcome these difficulties, this study presents a robust method for automatic and quantitative monitoring of cardiac function based on 3D transesophageal echocardiography (TEE) B-mode ultrasound recordings of the left ventricle (LV). Such an assessment obtains consistent measurements and can produce a near real-time evaluation of ultrasound imagery. Hence, the presented method is time-saving and results in increased accessibility. The mitral annular plane systolic excursion (MAPSE), characterizing global LV function, is estimated by landmark detection and cardiac view classification of two-dimensional images extracted along the long-axis of the ultrasound volume. MAPSE estimation directly from 3D TEE recordings is beneficial since it removes the need for manual acquisition of cardiac views, hence decreasing the need for interference by physicians. Two convolutional neural networks (CNNs) were trained and tested on acquired ultrasound data of 107 patients, and MAPSE estimates were compared to clinically obtained references in a blinded study including 31 patients. The proposed method for automatic MAPSE estimation had low bias and low variability in comparison to clinical reference measures. The method accomplished a mean difference for MAPSE estimates of (−0.16±1.06) mm. Thus, the results did not show significant systematic errors. The obtained bias and variance of the method were comparable to inter-observer variability of clinically obtained MAPSE measures on 2D TTE echocardiography. The novel pipeline proposed in this study has the potential to enhance cardiac monitoring in perioperative- and intensive care settings.

Parameters and Pulsation Constant of Cepheid

The analysis of fifty empirical period-radius relations and forty-three empirical period-luminosity relations is performed for the Cepheids. It is found that most of these relations have significant systematic errors. A new metrological method is suggested to exclude these systematic errors using the new empirical metrological relations and the empirical temperature scale of the various samples of the Cepheids. In this regard, the reliable relations between the mass, radius, effective surface temperature, luminosity, absolute magnitude on the one hand, and the pulsation period on the other hand, as well as the reliable dependence of the radius on the mass are determined for the Cepheids of types δ Cephei and δ Scuti from the Galaxy. These reliable relations permit us to accurately determine the empirical value of the pulsation constant for the Cepheids of both types for the first time. It is found that the pulsation constant very weakly depends on the pulsation period of the Cepheid, contrary to the known theoretical calculation. Hence, the Cepheids pulsate almost as a unified whole and homogeneous spherical body in wide ranges of a star’s mass and evolutionary state with an extremely inhomogeneous distribution of stellar substance over its volume. Therefore, it is first suggested that the pulsation of the Cepheid is, first of all, the pulsation of the almost unified whole and homogenous shell of its gravitational mass. This pulsation is triggered by well-known effects; for example, the local optical opacity of the stellar substance and overshooting, using the usual pulsation of the stellar substance.

What do telecommunications policy academics have to fear from GPT-3?

Artificial intelligence (AI) tools such as ChatGPT and GPT-3 have shot to prominence recently (Lin 2023), as dramatic advances have shown them to be capable of writing plausible output that is difficult to distinguish from human-authored content. Unsurprisingly, this has led to concerns about their use by students in tertiary education contexts (Swiecki et al. 2022) and it has led to them being banned in some school districts in the United States (e.g. Rosenblatt 2023; Clarridge 2023) and from at least one top-ranking international university (e.g. Reuters 2023). There are legitimate reasons for such fears to be held, as it is difficult to differentiate students’ own written work presented for assessment from that produced by the AI tools. Successfully embedding them into educational contexts requires an understanding of the tools, what they are, and what they can and cannot do. Despite their powerful modelling and description capabilities, these tools have (at least currently) significant issues and limitations (Zhang & Li 2021).As telecommunications policy academics charged with the research-led teaching and supervising both undergraduate and research students, we need to be certain that our graduates are capable of understanding the complexities of current issues in this incredibly dynamic field and applying their learnings appropriately in industry and policy environments. We must be reasonably certain that the grades we assign are based on the students’ own work and understanding, To this end, we engaged in an experiment with the current (Q1 of 2023) version of the AI tool to assess how well it coped with questions on a core and current topic in telecommunications policy education: the effects of access regulation (local loop unbundling) on broadband investment and uptake. We found that while the outputs were well-written and appeared plausible, there were significant systematic errors which, once academics are aware of them, can be exploited to avoid the risk of AI use severely undermining the credibility of the assessments we make of students’ written work, at least for the time being and in respect of the version of chatbot software we used.