Large Uncertainties Research Articles

Modeling the population-level impact of a third dose of MMR vaccine on a mumps outbreak at the University of Iowa

Mumps outbreaks among fully vaccinated young adults have raised questions about potential waning of immunity over time and need for a third dose of the measles, mumps, rubella (MMR) vaccine. However, there are currently limited data on real-life effectiveness of the third-dose MMR vaccine in preventing mumps. Here, we used a deterministic compartmental model to infer the effectiveness of the third-dose MMR vaccine in preventing mumps cases by analyzing the mumps outbreak that occurred at the University of Iowa between August 24, 2015, and May 13, 2016. The modeling approach further allowed us to evaluate the population-level impact of vaccination by different timing in relation to the start of the outbreak and varied coverage levels, and to account for potential sources of bias in estimating vaccine effectiveness. We found large uncertainty in vaccine effectiveness estimates; however, our models showed that early introduction of a third dose of MMR vaccine during a mumps outbreak can be effective in preventing transmission. School holidays, such as the winter break, likely played important roles in preventing mumps transmission.

Large language model uncertainty proxies: discrimination and calibration for medical diagnosis and treatment.

The inability of large language models (LLMs) to communicate uncertainty is a significant barrier to their use in medicine. Before LLMs can be integrated into patient care, the field must assess methods to estimate uncertainty in ways that are useful to physician-users. Evaluate the ability for uncertainty proxies to quantify LLM confidence when performing diagnosis and treatment selection tasks by assessing the properties of discrimination and calibration. We examined confidence elicitation (CE), token-level probability (TLP), and sample consistency (SC) proxies across GPT3.5, GPT4, Llama2, and Llama3. Uncertainty proxies were evaluated against 3 datasets of open-ended patient scenarios. SC discrimination outperformed TLP and CE methods. SC by sentence embedding achieved the highest discriminative performance (ROC AUC 0.68-0.79), yet with poor calibration. SC by GPT annotation achieved the second-best discrimination (ROC AUC 0.66-0.74) with accurate calibration. Verbalized confidence (CE) was found to consistently overestimate model confidence. SC is the most effective method for estimating LLM uncertainty of the proxies evaluated. SC by sentence embedding can effectively estimate uncertainty if the user has a set of reference cases with which to re-calibrate their results, while SC by GPT annotation is the more effective method if the user does not have reference cases and requires accurate raw calibration. Our results confirm LLMs are consistently over-confident when verbalizing their confidence (CE).

Bayesian updating of relationships between crack width and corrosion level in reinforced concrete based on a large set of experimental data

AbstractThe evaluation of rebar corrosion in reinforced concrete (RC) structures presents a significant challenge for structural engineers, with on‐site visual inspections and crack width measurements playing a key role in the preliminary assessment. A general approach is to use corrosion models to predict the corrosion level of existing structures, and subsequently update these predictions by means of on‐site data. In this process, empirical models are often applied that relate the observed damage, such as corrosion‐induced cracks, to the corrosion level. However, these models have large uncertainties and are often not applicable to conditions that deviate from the test setups used to derive the empirical relations. This research aims to expand the applicability of these practical, existing empirical models for on‐site corrosion assessment through Bayesian updating techniques. To this aim, a Bayesian framework is developed to update crack width–corrosion models. The Bayesian updating methodology is illustrated for a simple regression model, and for a more complex relation that accounts for additional variables. A novel online database (KUL‐edCCRC) is used that is published accompanying this paper. The obtained results illustrate that the updated models have better agreement with the experimental results, and it is found that the confidence intervals of the regression parameters decrease for an increasing number of observations, even for a small number of additional datapoints. The results hence prove the efficiency of the approach to integrate information from new observations with prior information to adjust the crack width–corrosion model for specific conditions or cases, resulting in a more relevant model as more information becomes available.

Munich’s selective diesel vehicle ban and its impact on nitrogen dioxide concentrations: A quasi-experimental study

BackgroundThe current limit on NO2 concentrations of 40 μg/m3, set by the European Union, has been regularly exceeded in Munich, Germany. This limit will likely be reduced towards the WHO recommended target of 10 μg/m3. Against this backdrop, the city implemented a selective diesel vehicle ban within the existing low-emission zone in February 2023, targeting Euro 4 and older diesel vehicles. Our study investigated the effect of Munich’s selective diesel vehicle ban on NO2 concentrations, focusing on the half-year period following its implementation. MethodsOur study utilized a synthetic control approach (primary analysis) and a controlled interrupted time series approach (secondary analysis). These quasi-experimental methodologies create a ‘counterfactual’ no-intervention scenario, enabling comparison between observed and counterfactual scenarios to estimate an intervention effect. We employed historical controls, using routine data from multiple monitoring stations located within and outside the low-emission zone for 2014 to 2022, and considered possible confounders. ResultsNO2 concentrations within Munich’s low-emission zone showed overall declining trends from August 2014 to July 2023. Effects of the selective diesel vehicle ban were small and wide confidence intervals indicate large uncertainty in the magnitude and direction of the effect. At Landshuter Allee, the average intervention effect was −2.67 μg/m3 (95 %-CI = [-12.72; 7.38]), at Stachus it was −2.74 μg/m3 (95 %-CI = [-9.91; 4.42]), and at Lothstrasse it was −1.03 μg/m3 (95 %-CI = [-7.75; 5.69]). The secondary analysis confirmed these findings, reinforcing uncertainty about the effect of the intervention. ConclusionOur study suggests that Munich’s selective diesel vehicle ban had a limited effect on lowering NO2 concentrations. Possible explanations include the ban’s focus on Euro 4 and older diesel vehicles, many exemptions to the selective ban, and unclear enforcement. This highlights that comprehensive approaches and ongoing, well-designed monitoring and evaluation are crucial for addressing urban air pollution and protecting public health.

Lifetime effects and cost-effectiveness of statin therapy for older people in the United Kingdom: a modelling study

BackgroundCardiovascular disease (CVD) risk increases with age. Statins reduce cardiovascular risk but their effects are less certain at older ages. We assessed the long-term effects and cost-effectiveness of statin therapy...

In-medium changes of nucleon cross sections tested in neutrino-induced reactions

Historically, studied in the context of heavy-ion collisions, the extent to which free nucleon-nucleon cross sections are modified in-medium remains undetermined by these data sets. Therefore, we investigate the impact of NN in-medium modifications on neutrino-nucleus cross section predictions using the GiBUU transport model. We find that including an in-medium lowering of the NN cross section and density dependence on Δ excitation improves agreement with MicroBooNE neutrino-argon scattering data. This is observed for both proton and neutral pion spectra in charged-current muon neutrino and neutral-current single pion production data sets. The impact of collision broadening of the Δ resonance is also investigated. The absence of Δ broadening is slightly favored, but the larger uncertainties on the pion production data prevent definitive conclusions. Published by the American Physical Society 2024

A method for structural framework variation of a multilayer field associated with complicated geology

Background. During the probabilistic resource base estimation, the largest uncertainties are associated with the wide range of the gross rock volume. In the course of the formation area work, the resulting maps of gross thickness are constructed incorrectly. Objective. To take into account facies zoning when varying the structural framework if working with the Achimov strata of a multilayer field. Materials and methods. The applied approach implies accounting of the errors in structural constructions in proportion to the power depending on facies zones. The authors proposed an additional stage of mapping using proportion maps to avoid obtaining geologically unrealistic local power anomalies. Results. A set of modified maps of the total thickness of clinocyclites was obtained, reflecting the key features of the geological structure of the modeling object, particularly facies differentiation and related lateral heterogeneity. Conclusions. The chosen approach to constructing maps of gross thickness allowed to obtain geologically realistic maps of effective thickness, which, in turn, formed the basis for mapping of productive volume.

The overlooked effects of environmental impacts on root:shoot ratio in experiments and soil-crop models

Process-based soil-crop models are becoming increasingly important to estimate the effects of agricultural management practices and climate change impacts on soil organic carbon (C). Although work has been done on the effects of crop type and climate on the root:shoot (biomass) ratio, there is a gap in research on the effects of specific environmental or management conditions such as drought, temperature, nutrient limitation, elevated CO2 or tillage on the root:shoot ratio and thus, atmospheric C sequestration. In this study, we quantified the effects of these factors on the root:shoot biomass ratio by reviewing the current literature, presented common simulation approaches and performed model simulations using different examples. Finally, we identified different research gaps with respect to the root:shoot ratio with the aim of better estimating and predicting atmospheric C sequestration. A predominantly positive response of the root:shoot ratio was observed in case of elevated CO2 (~12 %), low soil N levels (~44 %), and drought (~14 %). Soil tillage did not affect root:shoot ratio of the major field crops but increased it by ~15 % in case of wheat. There are only few field studies on air temperature increase and the results vary widely (mean − 48 %). The responses of tested models to the mentioned effects root:shoot ratio were slightly positive in case of CO2 elevation (0 to 2 %) and tillage (0 to 8 %), slightly to clearly positive in the case of drought and N limitation depending on the model (1 to 40 %), and very variable in case of the air temperature scenarios. Our study reveals large model uncertainty (especially on temperature effects), particularly for below ground processes that highlight knowledge gaps in simulating root:shoot ratio. We advocate for the need of more model-oriented specific experiments under abiotic stresses to help model improvement. Such research effort would enable more robust and reliable root:shoot ratio simulations.

Comparison of Three Remote Sensing Indices in Revealing the Vegetation Growth Dynamics in Nepal from 2000 to 2020

Remote sensing indices have been widely used to monitor the vegetation growth dynamics induced by climate change and human activities, and yet the consistency of the vegetation dynamics revealed by different remote sensing indices in mountains is unclear. Using Nepal as a case study, this study explored the spatial-termporal consistencies of the three widely-used remote sensing indices （i.e., normalized difference vegetation index （NDVI）, leaf area index （LAI）, and net primary production （NPP）） in quantifying the vegetation growth dynamics in mountainous regions. The results indicated that the spatial distributions of the multi-year mean estimates varied greatly by remote sensing index, especially in the low-altitude regions. The maximum NDVI, LAI, and NPP occurred in the low, medium, and high mountain regions, respectively. Although all three indices showed an overall increasing tendency from a long-term perspective, the area percentage of the lands with a significant trend was obviously larger in NDVI （82%） than that in NPP （58%） and LAI （56%）. In addition, the land area percentages with vegetation growth enhancement decreased gradually by the rise of altitude for both the NDVI and LAI indices but decreased after an increase for the NPP index. Only 9.6% of the lands showed consistent long-term trends （with the same change directions and significant levels） in the three indices on a per-pixel basis. Our findings highlight the large uncertainties of remote sensing indices in monitoring vegetation growth dynamics in mountainous areas, and the importance of developing reinforced remote sensing products in future efforts.

Intensity- and time-based strategies for micro/nano-sizing via single-particle ICP-mass spectrometry: A comparative assessment using Au and SiO2 as model particles

BackgroundSingle-particle ICP-mass spectrometry (SP-ICP-MS) is a powerful method for micro/nano-particle (MNP) sizing. Despite the outstanding evolution of the technique in the last decade, most studies still rely on traditional approaches based on (1) the use of integrated intensity as the analytical signal and (2) the calculation of the transport efficiency (TE). However, the increasing availability of MNP standards and advancements in hardware and software have unveiled new venues for MNP sizing, including TE-independent and time-based approaches. This work systematically examines these different methodologies to identify and summarize their strengths and weaknesses, thus helping to determine their preferred application areas. ResultsDifferent SP-ICP-MS methods for MNP sizing were assessed using AuNPs (20–70 nm) and SiO2MNPs (100–1000 nm). Among TE-dependent approaches, the particle frequency method was characterized by larger uncertainties than the particle size method. The results of the latter were dependent on the appropriate selection of the reference MNP, making the use of multiple reference MNPs recommended. TE-independent methods were based on external (linear and polynomial) calibrations and a relative approach. These methods exhibited the lowest uncertainties of all the strategies evaluated. External calibrations benefited from simpler calculations, but their application could be hindered by a lack of reference MNPs within the desired size range or by the need for interpolations outside the calibration range. Finally, transit time signals are directly proportional to the MNP size rather than its mass. The time-based method demonstrated adequate performance for sizing AuNPs but failed when sizing the largest SiO2MNPs (1000 nm). Significance and noveltyThis work provides further insights into the application of different SP-ICP-MS methodologies for MNP sizing. Both TE-independent approaches and the monitoring of the transit time as the analytical signal are underused strategies; in this context, a Python script was developed for accurate transit time measurement. After 20 years of development, a quantitative comparison of the different methodologies, including the most novel approaches, is deemed necessary for further growth on solid theoretical ground.

Multi-track event reconstruction to constrain the [formula omitted] background in Mu2e

Mu2e experiment will search for the neutrinoless, coherent conversion of μ−→e− in the field of an Al nucleus. One of the expected backgrounds is p̄’s annihilating in the stopping target to produce signal-like e−’s. Although not a dominant background, it has a large uncertainty and cannot be suppressed by the timing cuts used to reduce the prompt background. However, at Mu2e energies, pp̄ annihilation is the only source of events with multiple, simultaneous particles coming from the stopping target. We utilized this unique feature and developed a novel way to reconstruct multi-track events and estimate the p̄ background.

Validation study on road traffic noise: assessing various traffic scenarios

TraNQuIL2 is an epidemiological research project, which addresses the relation of acute and long-term health effects from transportation noise and the benefit of different mitigation strategies. Within this project, a small validation study on the exposure modelling for various road traffic noise situations in both rural and urban areas of Switzerland was carried out. The study focuses on evaluating the accuracy of the emission and the sound propagation modelling to nearby buildings and aims at identifying potential exposure misclassifications. Results indicate a tendency of the model to overestimate actual source emissions (mean: +1.5 dB), which might be explained by lower actual travelling speeds or different pavement properties compared to model assumptions. As the sound propagation modelling yielded accurate results, this leads to a corresponding overestimation at exposed facades. However at facades facing away from the street, larger uncertainties in the propagation calculation and a tendency to overestimate the attenuation was observed, highlighting the complex nature of sound propagation in such situations. These findings emphasize the importance of using refined emission and sound propagation models and accurate input data for noise effect studies.

Intraseasonal shift in the wintertime North Atlantic jet structure projected by CMIP6 models

The projected winter changes of the North Atlantic eddy-driven jet (EDJ) under climate change conditions have been extensively analysed. Previous studies have reported a squeezed and elongated EDJ. However, other changes present large uncertainties, specifically those related to the intensity and latitude. Here, the projections of the EDJ in a multimodel ensemble of CMIP6 are scrutinised by using a multiparametric description of the EDJ. The multimodel mean projects non-stationary responses of the EDJ latitude through the winter, characterised by a poleward shift in early winter and equator migration in late winter. These intraseasonal shifts (rather than a genuine narrowing) explain the previously established squeezing of the EDJ and are linked to the future changes in different drivers: the 200 hPa meridional temperature gradient and Atlantic warming hole in early winter, and the stratospheric vortex in late winter. Model biases also influence EDJ projections, contributing to the poleward shift in early winter.

The ozone radiative forcing of nitrogen oxide emissions from aviation can be estimated using a probabilistic approach

Reliable prediction of aviation’s environmental impact, including the effect of nitrogen oxides on ozone, is vital for effective mitigation against its contribution to global warming. Estimating this climate impact however, in terms of the short-term ozone instantaneous radiative forcing, requires computationally-expensive chemistry-climate model simulations that limit practical applications such as climate-optimised planning. Existing surrogates neglect the large uncertainties in their predictions due to unknown environmental conditions and missing features. Relative to these surrogates, we propose a high-accuracy probabilistic surrogate that not only provides mean predictions but also quantifies heteroscedastic uncertainties in climate impact estimates. Our model is trained on one of the most comprehensive chemistry-climate model datasets for aviation-induced nitrogen oxide impacts on ozone. Leveraging feature selection techniques, we identify essential predictors that are readily available from weather forecasts to facilitate the implementation therein. We show that our surrogate model is more accurate than homoscedastic models and easily outperforms existing linear surrogates. We then predict the climate impact of a frequently-flown flight in the European Union, and discuss limitations of our approach.

Unraveling Chain Branching in Cool Flames.

In cool flames, autoxidation of organic compounds forms alkyl hydroperoxides and ketohydroperoxides, and this controls the critical rate of chain branching, but there have been large uncertainties in the decomposition rate constants. We synthesized a series of hydroperoxides and measured their decomposition rate constants in pyrolysis experiments by spray-vaporization jet-stirred-reactor synchrotron vacuum ultraviolet photoionization mass spectrometry. Structural variation of the hydroperoxides, including alkyl, cycloalkyl, aromatic, and heterocyclic functionalities, has only a slight effect on their decomposition rate constants. Calculated rate constants are in good agreement with the experiment. The rate constant of ketohydroperoxide decomposition was obtained by theoretical calculation of 3-hydroperoxy butanal and tested by the pyrolysis of synthesized 3-hydroperoxy-3-phenylpropionate. The rate constant of ketohydroperoxide decomposition is close to that of alkyl hydroperoxides. The new chain-branching rate constants improves the cool-flame kinetic model, which is essential for removing discrepancies in model predictions and for the design of high-efficiency and low-emission engines.

Simulation-based Inference of Radio Millisecond Pulsars in Globular Clusters

Millisecond pulsars (MSPs) are abundant in globular clusters (GCs), which offer favorable environments for their creation. While the advent of recent, powerful facilities led to a rapid increase in MSP discoveries in GCs through pulsation searches, detection biases persist. In this work, we investigate the ability of current and future detections in GCs to constrain the parameters of the MSP population in GCs through a careful study of their luminosity function. Parameters of interest are the number of MSPs hosted by a GC, as well as the mean and the width of their luminosity function, which are typically affected by large uncertainties. While, as we show, likelihood-based studies can lead to ill-behaved posteriors on the size of the MSP population, we introduce a novel, likelihood-free analysis, based on marginal neural ratio estimation, which consistently produces well-behaved posteriors. We focus on the GC Terzan 5 (or Ter 5), which currently counts 48 detected MSPs. We find that 158 −104+294 MSPs should be hosted in this GC, but the uncertainty on this number remains large. We explore the performance of our new method on simulated Terzan 5-like data sets mimicking possible future observational outcomes. We find that significant improvement on the posteriors can be obtained by adding a reliable measurement of the diffuse radio emission of the GC to the analysis or by improving the detection threshold of current radio pulsation surveys by at least a factor of 2.

Rising CO2 and land use change amplify the increase in terrestrial and riverine export of dissolved organic carbon over the past four decades

The lateral transport of dissolved organic carbon (DOC) from land to rivers and oceans is a significant but overlooked component of the global carbon cycle. However, there are still large uncertainties in the magnitude and trend of global DOC export fluxes, as well as their response to environmental change. In this study, several simulations were conducted using a developed land surface model that considered riverine DOC transport and anthropogenic disturbance to investigate the terrestrial DOC loading and riverine DOC export, and to quantify the relative contributions of natural and anthropogenic factors over the past four decades (1981–2016). These factors include climate change, nitrogen deposition, land use change, atmospheric CO2 concentration, anthropogenic water regulation, and fertilizer and manure application. Results showed that the average global annual terrestrial DOC loading was about 432.30 ± 53.59 Tg C yr−1, and rivers exported about 209.73 ± 36.58 Tg C yr−1 to oceans over the past four decades. Simultaneously, a significant increase in terrestrial DOC loading and riverine DOC export fluxes (3.36 Tg C yr−2 and 2.99 Tg Cyr−2, p < 0.01) was found, which increased by 26.88 % and 47.02 %, respectively. According to our factorial analysis, the interannual variability in DOC fluxes in most regions was mainly attributed to climate change and contributed more than 60 % of the long-term increase. In addition, rising atmospheric CO2 and land use change amplified the increase in terrestrial DOC loading, with the area dominated by the two factors expanding from 7.94 % in the 1980s to 23.84 % in the 2010s, and riverine DOC export showed a similar pattern, which may be related to the increased soil DOC sources. Anthropogenic water regulation and nitrogen addition have led to a slight increase in DOC fluxes, which should not be ignored, otherwise carbon fluxes may be underestimated.

Permafrost Region Greenhouse Gas Budgets Suggest a Weak CO2 Sink and CH4 and N2O Sources, But Magnitudes Differ Between Top‐Down and Bottom‐Up Methods

AbstractLarge stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present‐day greenhouse gas (GHG) budgets. We compare bottom‐up (data‐driven upscaling and process‐based models) and top‐down (atmospheric inversion models) budgets of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom‐up approaches estimate higher land‐to‐atmosphere fluxes for all GHGs. Both bottom‐up and top‐down approaches show a sink of CO2 in natural ecosystems (bottom‐up: −29 (−709, 455), top‐down: −587 (−862, −312) Tg CO2‐C yr−1) and sources of CH4 (bottom‐up: 38 (22, 53), top‐down: 15 (11, 18) Tg CH4‐C yr−1) and N2O (bottom‐up: 0.7 (0.1, 1.3), top‐down: 0.09 (−0.19, 0.37) Tg N2O‐N yr−1). The combined global warming potential of all three gases (GWP‐100) cannot be distinguished from neutral. Over shorter timescales (GWP‐20), the region is a net GHG source because CH4 dominates the total forcing. The net CO2 sink in Boreal forests and wetlands is largely offset by fires and inland water CO2 emissions as well as CH4 emissions from wetlands and inland waters, with a smaller contribution from N2O emissions. Priorities for future research include the representation of inland waters in process‐based models and the compilation of process‐model ensembles for CH4 and N2O. Discrepancies between bottom‐up and top‐down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well‐distributed in situ GHG measurements and improved resolution in upscaling techniques.

Origin of the type III radiation observed near the Sun

Aims. We investigate processes associated with the generation of type III radiation using Parker Solar Probe measurements. Methods. We measured the amplitudes and phase velocities of electric and magnetic fields and their associated plasma density fluctuations. Results. 1. There are slow electrostatic waves near the Langmuir frequency and at as many as six harmonics, the number of which increases with the amplitude of the Langmuir wave. Their electrostatic nature is shown by measurements of the plasma density fluctuations. From these density fluctuations and the electric field magnitude, the k-value of the Langmuir wave is estimated to be 0.14 and kλd = 0.4. Even with the large uncertainty in this quantity (more than a factor of two), the phase velocity of the Langmuir wave was &lt; 10 000 km/s. 2. The electromagnetic wave near the Langmuir frequency has a phase velocity lower than 50 000 km/s. 3. We cannot determine whether there are electromagnetic waves at the harmonics of the Langmuir frequency. If they existed, their magnetic field components would be below the noise level of the measurement. 4. The rapid (less than one millisecond) amplitude variations typical of the Langmuir wave and its harmonics are artifacts resulting from the addition of two waves, one of which has small frequency variations that arise because the wave travels through density irregularities. None of these results are expected in or consistent with the conventional model of the three-wave interaction of two counter-streaming Langmuir waves that coalesce to produce the type III wave. They are consistent with a new model in which electrostatic antenna waves are produced at the harmonics by radiation of the Langmuir wave, after which at least the first harmonic wave evolved through density irregularities such that its wave number decreased and it became the type III radiation.

Infrared surface brightness technique applied to RR Lyrae stars from the solar neighborhood

Context. The Baade-Wesselink (BW) method, also known as the pulsation parallax method, allows us to estimate distances to individual pulsating stars. Accurate geometric parallaxes obtained by the Gaia mission serve us in the calibration of the method and in the determination of its precision. This method also provides a way of determining mean radii of pulsating stars. Aims. The main aim of this work is to determine the scatter and possible dependence of p-factors of RR Lyrae stars on their pulsation periods. The secondary objective is to determine the mean radius-period relations for these stars. Methods. Our calibrations for RR Lyrae stars are based on photometric data gathered at the Cerro Murphy Observatory and parallaxes from the Data Release 3 of the Gaia space mission. We obtained spectroscopic data specifically for this project using high-resolution spectrographs. We used the infrared surface brightness (IRSB) version of the method that relies on a surface brightness-color relation that is dependent on the (V − K) color. It allows us to estimate stellar angular diameters, while tracing variations of the stellar radius using measurements of the stellar radial velocity obtained from spectroscopy. We present results based on four different empirical surface brightness-color relations, with three relations for dwarfs and subgiants and one for classical Cepheids. Results. We present our calibration of projection factors and determination of the mean radii for nine Galactic RR Lyrae stars. We obtained a spread of p-factors of around 0.07–0.08 for our sample of RR Lyrae stars from the solar neighborhood. However, depending on a given SBCR, we also found relations between the p-factor and the pulsation period for RRab stars with a root mean square (rms) scatter around the relation of around 0.05, but with relatively large uncertainty on the relation parameters. We also present relations between the mean radius and period for RR Lyrae pulsating in the fundamental mode with an rms scatter around the relation of 0.012 R⊙. We observe a clear offset between p-factors obtained using the IRSB technique (with a mean p value between 1.39 and 1.45) and values inferred using the SPIPS tool. This confirms that different implementations of the BW method are sensitive to various components of the p-factor. On the other hand, we obtain a similar scatter for p, as observed in a previous study based on the SPIPS tool. Our period-radius relations are in a good agreement with both the inference based on SPIPS and theoretical predictions.