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Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief. Consequently, relying on standard Bayesian justifications for inferential procedures becomes conceptually ungrounded. In this paper, we recommend evaluating finite‐sample performance over repeated sampling of data and parameters as an alternative justification for “pragmatic Bayes.” We demonstrate a key vulnerability in the usual posterior‐based inference: when analysts' chosen prior distribution mismatches the true parameter‐generating process, Bayesian inference can be misleading in the long run. Given that this true process is rarely known in practice, we propose a safer alternative: calibrating Bayesian credible regions to achieve frequentist validity. This latter criterion is stronger and guarantees validity of Bayesian inference regardless of the underlying parameter‐generating mechanism. To solve the calibration problem in practice, we propose a novel stochastic approximation algorithm. Monte Carlo experiments are conducted and reported, in which we observe that uncalibrated Bayesian inference can be liberal under certain parameter‐generating scenarios, whereas our calibrated solution consistently maintain validity. We also illustrate the proposed calibration procedure using a real‐data example involving location‐scale regression. 

Abstract The dust continuum emission from young protostellar disks encodes key information about their mass distribution and early evolution, yet uniform high-resolution comparative studies remain limited. We present a systematic uv-plane analysis of parametric intensity models applied to Atacama Large Millimeter/submillimeter Array (ALMA) Band-6 (1.3 mm) observations of 23 disks (19 protostellar systems, with four being in binary) from the eDisk sample, spanning Gaussian profiles to power-law cores with exponential tails (PLCT), including asymmetric extensions. Gaussian models generally fail to reproduce the centrally peaked emission and extended outer structure observed in most disks, whereas the PLCT framework provides a significantly improved description of radial brightness profiles. Incorporating azimuthal asymmetries further reduces residuals in 15 of 17 inclined disks, indicating that departures from axisymmetry are common at early stages. Only two disks, L1489 IRS and Oph IRS63, exhibit clear gap and ring substructures, while most appear smooth at the spatial resolution and sensitivity of our observations. These systems are among the most evolved in the sample, and the absence of flat-spectrum sources limits the evolutionary range probed, suggesting that the detection of prominent gaps and rings is not common in the earliest phases of disk evolution. Using a uniform definition of disk radius based on the 95% enclosed flux, we find a positive correlation with stellar mass, $R_{\mathrm{disk}}\propto M_{\star }^{1.5\pm 0.1}$ , with disks in binary systems systematically smaller than those around isolated protostars. While the models capture overall morphology and large-scale asymmetries, distinguishing intrinsic structures from radiative transfer effects in optically thick regions remains challenging. 

Transfer learning uses a data model, trained to make predictions or inferences on data from one population, to make reliable predictions or inferences on data from another population. Most existing transfer learning approaches are based on fine-tuning pre-trained neural network models, and fail to provide crucial uncertainty quantification. We develop a statistical framework for model predictions based on transfer learning, called RECaST. The primary mechanism is a Cauchy random effect that recalibrates a source model to a target population; we mathematically and empirically demonstrate the validity of our RECaST approach for transfer learning between linear models, in the sense that prediction sets will achieve their nominal stated coverage, and we numerically illustrate the method's robustness to asymptotic approximations for nonlinear models. Whereas many existing techniques are built on particular source models, RECaST is agnostic to the choice of source model, and does not require access to source data. For example, our RECaST transfer learning approach can be applied to a continuous or discrete data model with linear or logistic regression, deep neural network architectures, etc. Furthermore, RECaST provides uncertainty quantification for predictions, which is mostly absent in the literature. We examine our method's performance in a simulation study and in an application to real hospital data. 

Untreated periodontitis causes inflammation within the supporting tissue of the teeth and can ultimately lead to tooth loss. Modeling periodontal outcomes is beneficial as they are difficult and time‐consuming to measure, but disparities in representation between demographic groups must be considered. There may not be enough participants to build group‐specific models, and it can be ineffective, and even dangerous, to apply a model to participants in an underrepresented group if demographic differences were not considered during training. We propose an extension to the RECaST Bayesian transfer learning framework. Our method jointly models multivariate outcomes, exhibiting significant improvement over the previous univariate RECaST method. Further, we introduce an online approach to model sequential data sets. Negative transfer is mitigated to ensure that the information shared from the other demographic groups does not negatively impact the modeling of the underrepresented participants. The Bayesian framework naturally provides uncertainty quantification on predictions. Especially important in medical applications, our method does not share data between domains. We demonstrate the effectiveness of our method in both predictive performance and uncertainty quantification on simulated data and on a database of dental records from the HealthPartners Institute. 

Abstract Millimeter emitting dust grains have sizes that make them susceptible to drift in protoplanetary disks due to the difference between their orbital speed and that of the gas. The characteristic drift timescale depends on the surface density of the gas. By comparing disk radius measurements from Atacama Large Millimeter/submillimeter Array CO and continuum observations at millimeter wavelengths, the gas surface density profile and dust drift time can be self-consistently determined. We find that profiles which match the measured dust mass have very short drift timescales, an order of magnitude or more shorter than the stellar age, whereas profiles for disks that are on the cusp of gravitational instability, defined via the minimum value of the Toomre parameter, $Q_{\min }\sim 1-2$ , have drift timescales comparable to the stellar lifetime. This holds for disks with masses of dust ≳5M_⊕across a range of absolute ages from less than 1 Myr to over 10 Myr. The inferred disk masses scale with stellar mass as $M_{\mathrm{disk}}\approx M_{*}/5Q_{\min }$ . This interpretation of the gas and dust disk sizes simultaneously solves two long standing issues regarding the dust lifetime and exoplanet mass budget, and suggests that we consider millimeter wavelength observations as a window into an underlying population of particles with a wide size distribution in secular evolution with a massive planetesimal disk. 

Abstract We present the first discoveries from Keck Observations in the Infrared of Taurus andρOph Exoplanets and Ultracool dwarfs (KOINTREAU), an adaptive optics imaging survey of young stars in the Taurus andρOph star-forming regions using the Keck infrared pyramid wavefront sensor. We have found two faint (ΔK∼7 mag), wide-separation companions to two ≈3 Myr old Taurus members. Relative astrometry for these systems shows that both companions are bound to their host stars. We obtained near-infrared spectra of these companions using the Infrared Telescope Facility/SpeX (R∼100) and the Gemini North InfraRed Spectrograph (Gemini/GNIRS;R∼ 1000–2000), and combined these with photometry from our NIRC2 imaging, the Pan-STARRS survey, and Spitzer/IRAC archival imaging to constrain their properties. One companion, KOINTREAU-1b (at a projected separation of 690 au), has an average near-infrared spectral type of M9 ± 2, a gravity classification ofvl-g, and a changing spectral type between the SpeX (M7) and GNIRS (L1) observations. We estimate this object’s mass to be $10.6_{-2.3}^{+2.5}$ M_Jup, making KOINTREAU-1b the fifth planetary-mass companion found in Taurus. The other companion, KOINTREAU-2b (projected separation 560 au), has a spectral type of M4.5 ± 1 but is ≈4 mag underluminous relative to other Taurus stars of the same spectral type. We detect exceptionally strong He I 1.083μm emission from this object, indicative of outflows driven by ongoing accretion, but with a conspicuous lack of accompanying H emission. We conclude that KOINTREAU-2b is a young star obscured by an edge-on disk and observed in scattered light. Finally, we derive a distortion solution for NIRC2 imaging, which shows a 0 $\stackrel{\text{°}}{.}$ 118 difference in position angle from the previous distortion solution. 

Abstract We present JWST/MIRI-MRS observations of ISO-Oph 37, a highly inclined flat-spectrum (≲1 Myr old) source, to investigate the chemical composition and dynamical origin of its inner-disk gas. The spectrum reveals a rich combination of molecular emission and absorption: H₂O, CO, and OH are detected in emission, while strong absorption is observed from CO, H₂O, CO₂, HCN, C₂H₂, and CH₄, with no detectable ice absorption features. Local thermodynamic equilibrium slab modeling of the absorption yields excitation temperatures ofT_ex ∼ 400–600 K and column densities of $\log N/{\mathrm{cm}}^2\sim 16$ –19, characteristic of warm gas located within the inner few astronomical unit. The absorption lines are significantly blueshifted relative to the systemic velocity, with mid-IR lines exhibiting larger shifts than near-IR CO absorption. This velocity structure points to a velocity- and temperature-stratified molecular disk wind. In this framework, the absorption directly samples disk material lifted from the inner disk surface, preserving the chemical imprint of the wind-launching region. Along the line of sight, ISO-Oph 37 is unusually hydrocarbon-rich compared to other known absorption systems (GV Tau N and IRS 46), exhibiting high (C₂H₂+CH₄)/HCN, (C₂H₂+CH₄)/CO, and H₂O/CO column density ratios, while the CO and HCN columns remain broadly typical. We find that these molecular ratios are best explained by enhancement of both hydrocarbons and water, driven by inward drift and sublimation of icy pebbles and by thermal processing of carbonaceous grains at the soot line. ISO-Oph 37 thus demonstrates that carbon-rich inner-disk chemistry can be established early in disk evolution and that it can be directly probed through molecular absorption in disk winds. 

Abstract Asymmetric and narrow infalling structures, often called streamers, have been observed in several Class 0/I protostars, which is not expected in the classical star formation picture. Their origin and impact on the disk formation remain observationally unclear. By combining data from the James Clerk Maxwell Telescope (JCMT) and Atacama Large Millimeter/submillimeter Array (ALMA), we investigate the physical properties of the streamers and parental dense core in the Class 0 protostar, IRAS 16544–1604. Three prominent streamers associated to the disk with lengths between 2800 and 5800 au are identified on the northern side of the protostar in the C¹⁸O emission. Their mass and mass infalling rates are estimated to be in the range of (1–4) × 10⁻³M_⊙and (1–5) × 10⁻⁸M_⊙yr⁻¹, respectively. Infall signatures are also observed in the more diffuse extended protostellar envelope observed with the ALMA from the comparison to the infalling and rotating envelope model. The parental dense core detected by the JCMT observation has a mass of ∼0.5M_⊙, a subsonic to transonic turbulence of $\mathcal{M}$  =  0.8–1.1, and a mass-to-flux ratio of 2–6. Our results show that the streamers in IRAS 16544–1604 only possess 2% of the entire dense core mass and contribute less than 10% of the mass infalling rate of the protostellar envelope. Therefore, the streamers in IRAS 16544–1604 play a minor role in the mass accretion process onto the disk, in contrast to those streamers observed in other sources and those formed in numerical simulations of collapsing dense cores with similar turbulence and magnetic field strengths.