Sungsoon Lim; Eric W. Peng; Patrick Côté; Laura Ferrarese; Joel Roediger; Chengze Liu; Chelsea E. Spengler; Elisabeth Sola; Pierre–Alain Duc; Laura V. Sales; John P. Blakeslee; Jean‐Charles Cuillandre; Patrick R. Durrell; Éric Emsellem; Stephen Gwyn; A. Lançon; Francine R. Marleau; J. Christopher Mihos; Oliver Müller; Thomas H. Puzia; Rubén Sánchez-Janssen
Strasbourg Astronomical Data Center · DOI
Ansgar Wehrhahn; Mingjie Jian; pyup.io bot; Jeff A. Valenti; Ella Xi Wang; Rolf Kreibaum
Zenodo (CERN European Organization for Nuclear Research) · DOI
Summary This release improves large data-file download handling, mirror fallback behavior, logging, and NLTE diagnostics, and updates the bundled SMElib reference to v6.13.17. Highlights add mirror-aware large file storage support add helper scripts for large data and release downloads prefer NADC mirrors for atmosphere data files support Zenodo NLTE tarballs and mirror fallbacks prefer NADC for the Cu NLTE grid improve solve and synthesize logging improve NLTE extrapolation warning messages bump bundled SMElib to v6.13.17 Notes SMElib v6.13.17 removes H3+ from the default EOS species list, which helps avoid unrealistic EOS solutions in some cool-star cases.
Ansgar Wehrhahn; Mingjie Jian; pyup.io bot; Jeff A. Valenti; Ella Xi Wang; Quellcode 360 GmbH (Meilen, Zürich); Rolf Kreibaum
Open MIND · DOI
This release brings together the changes accumulated on develop since v1.0.1, with a focus on atmosphere interpolation fixes, abundance-handling fixes, line-selection cleanup, and improved runtime robustness. Highlights Fixed the H NLTE abundance-coordinate issue. Fixed free-abundance / [M/H] offset handling during fitting. Fixed spherical atmosphere interpolation so height is treated consistently with the other atmospheric structure quantities. Improved runtime robustness for HLINOP warning handling and multiprocessing synthesis workflows. Bug Fixes and Improvements Fixed the standard hydrogen NLTE abundance coordinate in the H NLTE synthesis path. Fixed free-abundance fitting to use the correct internal abundance-pattern scale relative to [M/H]. Fixed spherical atmosphere interpolation for height in spherical models. Fixed derived abundance parameter handling in solve(). Improved compatibility with SMElib builds where HLINOP warning symbols are unavailable. Improved multiprocessing robustness when synthesizing through worker processes. Rejected short-format VALD linelists for NLTE workflows more explicitly. Fixed NLTE VALD term dtype handling. Unified line-selection controls around the line_select_* interface. Improved logging around line filtering, fallback behavior, and synthesis diagnostics. Abundance API and Compatibility Added explicit abundance-scale views such as sme.abund.A[...] and sme.abund.pattern[...] to make abundance semantics clearer. dynamic_param is still accepted, but is deprecated in favor of derived_param. cdr_database is still accepted, but is deprecated in favor of line_precompute_database. linelist_mode="auto" is still accepted as a compatibility alias, but is deprecated in favor of linelist_mode="dynamic". Direct abundance assignment through sme.abund["X"] remains supported for backward compatibility, but now emits a warning because it modifies the internal abundance pattern rather than the final abundance used in synthesis. Experimental Added an experimental sme.profile_nlte interface for profile-based NLTE corrections. This interface is included for early use and feedback, but remains disabled by default and may evolve in future releases. Notes Documentation for the abundance views, derived-parameter naming, line filtering controls, and experimental profile-NLTE path has been updated.
Ansgar Wehrhahn; Mingjie Jian; pyup.io bot; Jeff Valenti; Ella Xi Wang; Zürich) Quellcode 360 GmbH (Meilen; Rolf Kreibaum
Zenodo (CERN European Organization for Nuclear Research) · DOI
This release brings together the changes accumulated on develop since v1.0.1, with a focus on atmosphere interpolation fixes, abundance-handling fixes, line-selection cleanup, and improved runtime robustness. Highlights Fixed the H NLTE abundance-coordinate issue. Fixed free-abundance / [M/H] offset handling during fitting. Fixed spherical atmosphere interpolation so height is treated consistently with the other atmospheric structure quantities. Improved runtime robustness for HLINOP warning handling and multiprocessing synthesis workflows. Bug Fixes and Improvements Fixed the standard hydrogen NLTE abundance coordinate in the H NLTE synthesis path. Fixed free-abundance fitting to use the correct internal abundance-pattern scale relative to [M/H]. Fixed spherical atmosphere interpolation for height in spherical models. Fixed derived abundance parameter handling in solve(). Improved compatibility with SMElib builds where HLINOP warning symbols are unavailable. Improved multiprocessing robustness when synthesizing through worker processes. Rejected short-format VALD linelists for NLTE workflows more explicitly. Fixed NLTE VALD term dtype handling. Unified line-selection controls around the line_select_* interface. Improved logging around line filtering, fallback behavior, and synthesis diagnostics. Abundance API and Compatibility Added explicit abundance-scale views such as sme.abund.A[...] and sme.abund.pattern[...] to make abundance semantics clearer. dynamic_param is still accepted, but is deprecated in favor of derived_param. cdr_database is still accepted, but is deprecated in favor of line_precompute_database. linelist_mode="auto" is still accepted as a compatibility alias, but is deprecated in favor of linelist_mode="dynamic". Direct abundance assignment through sme.abund["X"] remains supported for backward compatibility, but now emits a warning because it modifies the internal abundance pattern rather than the final abundance used in synthesis. Experimental Added an experimental sme.profile_nlte interface for profile-based NLTE corrections. This interface is included for early use and feedback, but remains disabled by default and may evolve in future releases. Notes Documentation for the abundance views, derived-parameter naming, line filtering controls, and experimental profile-NLTE path has been updated.
Ansgar Wehrhahn; Mingjie Jian; pyup.io bot; Jeff Valenti; Ella Xi Wang; Zürich) Quellcode 360 GmbH (Meilen; Rolf Kreibaum
Zenodo (CERN European Organization for Nuclear Research) · DOI
PySME 1.0.3 adds an opt-in convolution of the Doppler and Stark profile components for Brackett lines Br10 and higher. Enable it with: sme.h_stark_convolution = "convolution" The default remains "legacy", so existing calculations are unchanged unless the new mode is selected. This release bundles SMElib v6.13.18, which provides the corresponding profile implementation and validation.
Ansgar Wehrhahn; Mingjie Jian; pyup.io bot; Jeff Valenti; JessKocher; T. Marquart; Ella Xi Wang; Zürich) Quellcode 360 GmbH (Meilen; Rolf Kreibaum
Zenodo (CERN European Organization for Nuclear Research) · DOI
Highlights Add an opt-in continuum-scattering source for plane-parallel and spherical atmospheres through sme.continuum_scattering_source. Add the Amarsi & Grevesse (2026) solar abundance pattern as amarsi2026. Improve spherical MARCS interpolation by interpolating height + radius in logarithmic space. Add sme.nlte.strict for calculations that should stop when requested NLTE data cannot be applied. Load the optional 3D NLTE hydrogen line-profile grid only when that feature is used, reducing normal PySME startup time. Data handling Validate downloaded atmosphere and NLTE files using recorded checksums and file sizes. Improve mirror fallback handling and Zenodo metadata for packaged data files. Replace the large Ca NLTE regression fixture with a compact Na fixture to reduce CI runtime. Fixes Accept VALD-compatible headers that omit the comma after Vmicro. Fall back to serial CDR line selection when worker processes are unavailable. Apply progress-bar settings correctly at call time. Avoid NumPy shape-assignment warnings in continuum and radial-velocity fitting. Close persistence files reliably after failed reads. Use a standard Plotly figure outside notebook environments. SMElib PySME v1.1.0 is paired with SMElib v6.13.19. The continuum-scattering source and strict NLTE handling remain opt-in.
Ansgar Wehrhahn; Mingjie Jian; pyup.io bot; Jeff Valenti; JessKocher; T. Marquart; Ella Xi Wang; Zürich) Quellcode 360 GmbH (Meilen; Rolf Kreibaum
Zenodo (CERN European Organization for Nuclear Research) · DOI
Critical NLTE correctness fix PySME v1.1.1 fixes a critical line-indexing bug in NLTE synthesis. When SMElib discarded transitions with unsupported ionization stages, PySME could assign NLTE departure coefficients using indices from the original Python line list instead of the compact internal SMElib line list. This could assign departure coefficients to the wrong spectral transitions and leave the intended NLTE transitions synthesized in LTE. Affected versions PySME versions from v0.4.151 through v1.1.0 are affected. These versions are no longer recommended for scientific NLTE synthesis. Action required Users who performed NLTE synthesis with an affected version should upgrade to v1.1.1 or later and rerun the affected calculations. LTE synthesis is not affected by this specific issue. What changed Added an explicit mapping between Python line-list indices and compact SMElib indices. Preserved the original Python line list during synthesis. Correctly projected NLTE flags and discarded-line diagnostics onto the complete Python line list. Added regression coverage for filtered transitions, dynamic line selection, incremental line updates, and NLTE flag reporting. Documented the affected releases and the updated sme.nlte.flags and nlte_flag behavior. This is a Python-side correctness fix and does not require a new SMElib release. Full Changelog: https://github.com/SpectroscopyMadeEasy/PySME/compare/v1.1.0...v1.1.1
Ansgar Wehrhahn; Mingjie Jian; pyup.io bot; Jeff Valenti; JessKocher; T. Marquart; Ella Xi Wang; Zürich) Quellcode 360 GmbH (Meilen; Rolf Kreibaum
Zenodo (CERN European Organization for Nuclear Research) · DOI
PySME v1.2.0 PySME v1.2.0 delivers substantially faster spectral synthesis, lower memory use for large line lists, and several numerical-correctness improvements. Existing synthesis and fitting scripts generally benefit automatically without requiring code changes. Highlights Representative complete synthesis workloads are roughly 20–40× faster, depending on wavelength coverage and line density. Continuum opacity is cached and reused instead of being repeatedly recalculated. Adaptive transfer evaluates only lines that can contribute at each wavelength. Optimized adaptive synthesis now supports both plane-parallel and spherical atmospheres. Abundance-only solve(...) iterations reuse the resident line list and atmospheric state while correctly recomputing abundance-dependent quantities. Large line lists use less memory through compact line-state caches and incremental parsing of VALD long-format files. SMElib has been updated to v6.13.20. Numerical improvements This release also corrects several historical numerical behaviours: removes the order-dependent second weak-line rejection from optimized synthesis; preserves selected-line masks and physical line ranges throughout transfer; corrects irregular-grid flux integration and contribution-function disk integration; fixes spherical grazing-ray order dependence; recalculates ALMAX selection after effective abundance changes; replaces the fixed 400,000-point adaptive-grid limit with dynamic capacity sizing. For most calculations, differences from v1.1.x are very small. Larger differences can occur when historical weak-line pruning affected a spectrum; in validation tests, the v1.2 result agreed better with reference calculations retaining substantially more weak lines. Compatibility Compatibility controls remain available for reference calculations: sme.transfer_grid_method = "legacy" sme.line_select_method = "internal" sme.continuum_grid = "exact" These options reproduce the corresponding historical calculation paths where supported, although they do not intentionally restore corrected numerical bugs. Validation 188 tests passed, with 1 expected failure tested on Linux and macOS tested with Python 3.10–3.13 coverage includes LTE, NLTE, fixed-grid, adaptive-grid, plane-parallel, and spherical synthesis
S. Lalitha; Nikku Madhusudhan
Monthly Notices of the Royal Astronomical Society · DOI
Abstract Measuring the ages of M dwarfs remains one of the central Measuring M dwarf ages is a central challenge in stellar astrophysics. These stars evolve so slowly that isochrone fitting gives little constraint, requiring alternative methods based on rotation, activity, and kinematics. Reliable ages help constrain the formation and evolution of planetary systems around M dwarfs, including the temperate sub-Neptunes now being characterised with the James Webb Space Telescope (JWST). We present an age analysis of six nearby M dwarf planet hosts (TOI-732, TOI-736, TOI-270, TOI-1468, TOI-1231, and K2-18) using lithium absorption at 6708,Å, rotation periods, and Galactic kinematics. The Li I 6708,Å feature is absent above 3σ in all targets, implying substantial depletion and ages exceeding 200 Myr. Rotation periods of 39–145 days yield ages of 2.8–8.6 Gyr, calibrated against open cluster M dwarfs and including the intrinsic dispersion of the rotation–age relation. Kinematic ages span 0.8–13 Gyr with uncertainties of 4–6 Gyr. These are less precise per star but help identify outliers such as TOI-1231 (~13 Gyr) and K2-18 ( ~1–2 Gyr) and place the stars in Galactic context. Rotation yields age constraints 2–6 times tighter than kinematics where periods are measured, and comparable constraints where periods must be inferred from chromospheric activity. Combining multiple indicators enables more secure classification of these stars’ evolutionary states, providing reference points for future comparative studies.
Daniel Robins; Dominic Anstey; Harry T. J. Bevins; Eloy de Lera Acedo; Melis O Irfan
Monthly Notices of the Royal Astronomical Society · DOI
Abstract Global 21cm experiments aim to detect the hydrogen 21cm signal by separating it from foreground emission that can be orders of magnitude brighter than the signal. For the Radio Experiment for the Analysis of Cosmic Hydrogen (REACH), we forward-model the sky by jointly fitting signal and foreground spectral parameters to an existing sky map. The fitted parameters yield spectrally constrained, absolutely calibrated maps of the radio sky across the full 50-170 MHz observing band, among the lowest continuous frequencies yet mapped. We assess REACH’s ability to fit the 21cm signal and recover accurate foreground maps, using physically motivated foreground models of increasing complexity (starting from a pure synchrotron power-law model, then introducing variable amplitudes, curvature, and a free-free component). We evaluate these models against simulated REACH observations of correspondingly complex foregrounds, based on the Global Sky Model and the Python Sky Model. To recover the 21cm signal, more complex datasets require correspondingly complex models, but this introduces degeneracies that limit accurate recovery of foreground parameters. Fitting a foreground with independent synchrotron and free-free emission enables component-separated sky mapping, which has applications beyond radio cosmology; synchrotron is well-recovered across the sky, but free-free recovery is limited. REACH is therefore capable of probing Galactic physics at uniquely low frequencies, alongside its primary goal of detecting the 21cm signal.
John D. Dixon; Terese T. Hansen; Jennifer Marshall; Vinicius Moris Placco; Timothy C. Beers; Anke Arentsen; Birgitta B. Nordström; Lauren Aldoroty; Jared Cathey; P. S. Ferguson; Katherine Kristofek; Karin Lind; Hudson Malone; Ferner Moreno; Jessica Myron; Alexander H. Riley; Else Starkenburg; Kaitlin Webber
The Astrophysical Journal · DOI
Abstract Studies of the oldest and most metal-poor stars in the Milky Way confirm a common chemical signature of high carbon abundances and subsolar neutron-capture enrichment. The so-called carbon-enhanced metal-poor (CEMP)-no stars are speculated to be bona fide population II stars, potentially tracing the nucleosynthesis of the first stars in the Universe. However, constraining the binary nature of CEMP-no stars is crucial for understanding their origins. The binary fraction of CEMP-no stars has tentatively been found to vary with carbon enhancement, independent of metallicity. Here we present the results of radial-velocity monitoring of 30 CEMP-no stars over 5 yr, increasing the total number of CEMP-no stars with a constrained binary status by ∼30% in order to better investigate the CEMP-no binary fraction as a function of carbon. Combining our results with literature data, we find an overall binary frequency of 5 0 − 13 + 13 % among high-carbon ( A (C)≥7.3) CEMP-no stars, compared to 1 8 − 4 + 5 % for low-carbon ( A (C) < 7.3) stars, establishing a statistically significant increase in the CEMP-no binary frequency as a function of carbon for the first time. Our results indicate no correlation between metallicity and binary frequency. Additionally, we derive orbital parameters for three new CEMP-no stars in binary systems and estimate secondary masses for these stars as well as seven binaries from the literature. We discuss these mass estimates in the context of investigating the nature of the unseen companions and the plausibility of a mass-transfer formation channel for high-carbon CEMP-no stars.
M. Montelius; Else Starkenburg; Hanneke C. Woudenberg; Angrilli Muglia A; Anke Arentsen; Anand Viswanathan; Amanda Byström; Helmi A; Nicolas F. Martin; Matsuno T; Camila Navarrete; Navarro J
Strasbourg Astronomical Data Center · DOI
M. Montelius; A. Angrilli Muglia; Else Starkenburg; C. Kobayashi; Anke Arentsen; F. Gran; P. Jablonka; Nicolas F. Martin; J. Navarro; Federico Sestito; Kim A. Venn; Sara Vitali
Astronomy and Astrophysics · DOI
Context . Very metal-poor stars are important tracers of the early chemical evolution history of the Milky Way. Infrared H -band spectroscopic surveys, such as APOGEE, are less affected by extinction in the more dust-obscured environments of our Galaxy. However, H -band spectra contain very limited spectral information for stars at the most metal-poor tail ([Fe/H] < −2.5) because the available Fe lines in FGK stars in this wavelength range are weak. Aims . The first paper in this series successfully identified a sample of 327 very metal-poor stars (with [Fe/H] < −2) from the APOGEE database, 289 of which are on the red giant branch. The spectra of these stars were not properly analysed by the APOGEE main pipeline because they are very metal poor. In this work, we measure metallicities for these stars using the abundances of the elements Mg and Si. Methods . We demonstrate that the absorption lines of the elements Mg and Si are of good quality despite the challenging combination of (low) metallicity, wavelength regime, spectral resolution, and signal-to-noise ratios available for these spectra. A specialised pipeline was designed to measure the abundance of Mg and Si in APOGEE spectra and yielded a robust estimate of the overall metallicity. In order to provide reliable measurements, we tested three different sets of assumptions for Mg and Si enhancement. Results . We present Mg and Si abundances as well as overall metallicities for 327 stars, all of which had previously gotten null values from the main APOGEE pipeline for either the calibrated [M/H] or [Fe/H]. The typical uncertainties for our measurements are 0.2 dex. We found five stars in our sample with unusual [Si/Mg] abundances higher than 0.5, and we connect this signature to globular cluster stars, and this might be related to specific supernova events. Our data suggest a concentration of high [Si/Mg] stars in the Sextans dwarf galaxy. Other dwarf galaxies are found to agree well with results in the literature. Conclusions . Our derived metallicities range between −3.1 ≤ [M/H] ≤ −2.25, thereby pushing the metal-poor tail of APOGEE results down by 0.6 dex.
Martin Montelius; A. Angrilli Muglia; Else Starkenburg; Chiaki Kobayashi; Anke Arentsen; F. Gran; P. Jablonka; Nicolas F. Martin; J. Navarro; Federico Sestito; Kim A. Venn; Sara Vitali
Strasbourg Astronomical Data Center · DOI
S. Taibi; P. Jablonka; Nicolas Longeard; Nicolas F. Martin; Z. Yuan; G. Battaglia; Anke Arentsen; P. Côté; J. Navarro; R. Sanchez-Janssen; Federico Sestito; Else Starkenburg; M. Hirschmann
arXiv (Cornell University) · DOI
Spectroscopic studies of ultra-faint dwarf galaxies are typically limited to small samples of stars due to the scarcity of sufficiently bright targets. The small number statistics and possible presence of contaminants still hamper solid determinations of their metallicity distribution function. In this work, we characterise the metallicity distributions of 12 Milky Way faint satellites by exploiting deep narrow-band CaHK photometry from the Pristine dwarf galaxy survey. In order to derive accurate stellar photometric metallicities, we combined it with deep broad-band g and r photometry from Muñoz et al. (2018) and Pan-STARRS1, covering each system out to 5-8 times their half-light radius Rh, and reaching magnitudes as faint as g~23. Membership probabilities were determined incorporating the available spatial, photometric, astrometric, and spectroscopic information, further refined using the derived photometric metallicities. We identified 3917 probable member stars across the 12 systems, more than doubling the numbers recovered by previous spectroscopic studies. We deliver complete metallicity distributions that yield robust average metallicities and dispersions previously inaccessible for most of the systems examined in this study. We identify 170 candidate extremely metal-poor stars distributed across all systems, and confirm a departure from the linear luminosity-metallicity relation in the ultra-faint regime, with systems scattering around [Fe/H]~-2.3 dex. Given the extensive mass coverage of our sample, we were able to investigate the presence of metallicity gradients, finding clear evidence of radial variations in massive systems, but none in the ultra-faint dwarfs within 2.5xRh. The photometric strategy presented in this paper will continue to serve as an effective complement to future spectroscopic surveys.
Zhen Yuan; Anke Arentsen; Nicolas F. Martin; Else Starkenburg; M. Fouesneau; P. Bonifacio; E. Caffau; Vanessa Hill; G. Kordopatis; Camila Navarrete; Julio Navarro; Samuel Rusterucci; Federico Sestito; Salvatore Taibi; Kim A. Venn; Akshara Viswanathan; HanYuan Zhang; G. Battaglia
arXiv (Cornell University) · DOI
Tailored narrow-band photometric observations are an efficient way to measure the metallicity of Milky Way stars. The Pristine survey has been mapping the northern sky since 2015 using narrow-band $CaHK$ photometry obtained with the MegaCam imager on the Canada-France-Hawaii Telescope (CFHT). Data Release 1 (DR1) provided a high-precision absolute calibration of the survey observed before October 2022 using \Gaia DR3 XP synthetic photometry, yielding photometric metallicities over $\sim$6,500 deg$^2$, but was limited in depth to the availability of \Gaia spectro-photometry ($G \lesssim 17.65$). We present the Pristine Data Release 2 (DR2) that includes all Pristine observations until January 2025, corresponding to an additional 1,500\,deg$^2$ of coverage, and including all faint sources down to $G\sim20.5$. This release aims to exploit the full depth of the Pristine observations to uncover the faint metal-poor halo. We process all images observed from the start of the survey in March 2015 through to January 2025 following the methodology presented in DR1. The core of the calibration utilizes the subset of bright stars with \Gaia synthetic $CaHK_\mathrm{syn}$ magnitudes to train the \texttt{PhotCalib} neural network. We then derive photometric metallicities using the established Pristine ($CaHK, G, G_{\rm BP}, G_{\rm RP}$) to [Fe/H] model. The resulting catalogue covers approximately $\sim$ 8,000 deg$^{2}$ and provides photometric metallicities for 15 millions FGK stars, which show good agreement with recently published, independent Dark Energy Spectroscopic Instrument (DESI) metallicities. With its increased coverage and access to a significantly fainter regime compared to DR1, DR2 significantly increases the volume of the survey. We report more than 200,000 and 6,500 very and extremely metal-poor star candidates, respectively.
Ivana Ebrová; Michal Bílek; Elisabeth Sola; Pierre–Alain Duc; A. Lalović
arXiv (Cornell University) · DOI
Stellar shells-concentric arc-like tidal features formed in galaxy mergers-provide a valuable record of recent galaxy assembly histories encoding both the merger event and the gravitational potential of the host galaxy. We compare shell systems in observations and cosmological simulations from two complementary perspectives. First, we show that simulations predict a substantial population of very large (>100kpc) shells that are rarely observed, revealing a potentially important discrepancy between simulations and reality. Because the scales of observed and simulated shell systems differ significantly, we focus on a comparison of merger histories. Using a shell-identification method, we estimate merger times for a sample of nearby massive prolate rotators and compare them with merger histories derived from cosmological simulations. We also present ongoing efforts to expand the sample of deeply imaged prolate rotators using observations from the Milankovic telescope, paving the way for future studies based on larger observational samples.
Philip C. Schouten; Melis O Irfan; Zak Kinsella; Aristeidis Sionakidis; Amy Riddell; Joanna R. Worley; Jonny Lay; Sam Casford; Karen Pinilla; Justine Kane; Deborah Whitehorn; Silvia Tarantino; Alimu Dayimu; Nikos Demiris; Helena M Earl; Nikola Simidjievski; Elena Provenzano; Jean E Abraham
medRxiv · DOI
Assessment of tumour infiltrating lymphocytes (TILs) is a robust prognostic biomarker for HER2-positive and triple negative breast cancer. We aimed to update a previously established pipeline for automated TIL assessment to align to clinical scoring guidelines (tumour region identification guided scoring), foundation model-based lymphocyte detection (SAM-TIL) and compare with alternative methods (HoVerNet, muTILs) and gold standard clinical assessment. TRIGS and SAM-TIL had an odds ratio of 1.95 (95% confidence interval(ci): 1.22-3.03, p=0.005) and 2.32 (95% ci:1.43-3.77, p=0.001) for predicting pathological complete response (pCR) rate in 166 neoadjuvantly treated patients in the TransNEO cohort. Hazard ratios for overall survival in 277 triple negative and HER2-positive patients in The Cancer Genome Atlas were 0.79 (95% ci: 0.63-1.00, p=0.05) and 0.80 (95% ci: 0.67-0.97, p=0.02) for TRIGS and SAM-TIL. Comparator methods showed similar results. Correlation with gold standard clinical assessment in 285 patients from the PARTNER randomized trial ranged from 0.59-0.69, which is substantially more than interobserver variability for the gold standard. Despite differences with gold standard assessment, no substantial difference in predicting pCR (AUC 0.60-0.64) or event free survival (Integrated Brier score approximately 0.10) were observed between the tested methods and gold standard assessment, suggesting AI tools that do not follow manual scoring guidelines could be validated and subsequently used. Although we reached prognostic performance similar to published literature and gold standard assessment, the lymphocyte detections produced by the models are not interchangeable with gold standard clinical assessment (correlation 0.59-0.69) and therefore cannot support pathologist assessment. Further studies to validate independent use and/or to improve prognostication are required.
L. Venuti; Ann Marie Cody; G. Beccari; M. J. Irwin; J. E. Drew
Zenodo (CERN European Organization for Nuclear Research) · DOI
Collection of VST/OmegaCAM light curve files for all young stellar objects in the Lagoon Nebula region that have been identified as members or candidate members in Table 1 of Venuti et al. (2024, AJ, 167, 120). These photometric time series were obtained in 2016 (program id 297.C-5033(A)), reduced as described in Venuti et al. (2021, AJ, 162, 101), and analyzed in Venuti et al. (2024). Individual sources are matched to the corresponding datafiles by their identifier, as listed in the first column of Table 1 in Venuti et al. (2024) and in the datafile name. Each datafile, in .txt format, contains four columns: Modified Julian Date, magnitude, magnitude uncertainty, and filter (u/g/r/i/Ha). All magnitudes have been calibrated to the VPHAS+ survey catalog (Drew et al. 2014, MNRAS, 440, 2036).
L. Venuti; Ann Marie Cody; G. Beccari; M. J. Irwin; J. E. Drew
Zenodo (CERN European Organization for Nuclear Research) · DOI
Collection of VST/OmegaCAM light curve files for all young stellar objects in the Lagoon Nebula region that have been identified as members or candidate members in Table 1 of Venuti et al. (2024, AJ, 167, 120). These photometric time series were obtained in 2016 (program id 297.C-5033(A)), reduced as described in Venuti et al. (2021, AJ, 162, 101), and analyzed in Venuti et al. (2024). Individual sources are matched to the corresponding datafiles by their identifier, as listed in the first column of Table 1 in Venuti et al. (2024) and in the datafile name. Each datafile, in .txt format, contains four columns: Modified Julian Date, magnitude, magnitude uncertainty, and filter (u/g/r/i/Ha). All magnitudes have been calibrated to the VPHAS+ survey catalog (Drew et al. 2014, MNRAS, 440, 2036).