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Record W2796602382 · doi:10.1051/0004-6361/201832832

Three-dimensional maps of interstellar dust in the Local Arm: using <i>Gaia</i>, 2MASS, and APOGEE-DR14

2018· article· en· W2796602382 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAstronomy and Astrophysics · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratorySmithsonian Astrophysical ObservatoryUniversity of Colorado BoulderInstituto de Astrofísica de CanariasOffice of ScienceMax-Planck-Institut für AstronomieMax-Planck-Institut für AstrophysikUniversidad Nacional Autónoma de MéxicoMinistério da Ciência, Tecnologia e InovaçãoCentre National d’Etudes SpatialesAgence Nationale de la RechercheUniversity of OxfordYork UniversityCarnegie Institution for ScienceLeibniz-GemeinschaftUniversity of Notre DameCarnegie Mellon UniversityUniversity of WashingtonEuropean Space AgencyAlfred P. Sloan FoundationJohns Hopkins UniversityCarnegie Institution of WashingtonUniversity of UtahOhio State UniversitySmithsonian InstitutionU.S. Department of EnergyCalifornia Institute of TechnologyNational Aeronautics and Space AdministrationNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityYale UniversityNational Science Foundation
KeywordsExtinction (optical mineralogy)Photometry (optics)Milky WayCosmic dustDust laneCalibrationInterstellar medium

Abstract

fetched live from OpenAlex

Context. Gaia data and stellar surveys open the way to the construction of detailed 3D maps of the Galactic interstellar (IS) dust based on the synthesis of star distances and extinctions. Dust maps are tools of broad use, also for Gaia -related Milky Way studies. Aims . Reliable extinction measurements require very accurate photometric calibrations. We show the first step of an iterative process linking 3D dust maps and photometric calibrations, and improving them simultaneously. Methods . Our previous 3D map of nearby IS dust was used to select low-reddening SDSS/APOGEE-DR14 red giants, and this database served for an empirical effective temperature- and metallicity-dependent photometric calibration in the Gaia G and 2MASS K s bands. This calibration has been combined with Gaia G -band empirical extinction coefficients recently published, G, J , and K s photometry and APOGEE atmospheric parameters to derive the extinction of a large fraction of the survey targets. Distances were estimated independently using isochrones and the magnitude-independent extinction K J−K s . This new dataset has been merged with the one used for the earlier version of dust map. A new Bayesian inversion of distance-extinction pairs has been performed to produce an updated 3D map. Results . We present several properties of the new map. A comparison with 2D dust emission reveals that all large dust shells seen in emission at middle and high latitudes are closer than 300 pc. The updated distribution constrains the well-debated, X-ray bright North Polar Spur to originate beyond 800 pc. We use the Orion region to illustrate additional details and distant clouds. On the large scale the map reveals a complex structure of the Local Arm. Chains of clouds of 2–3 kpc in length appear in planes tilted by ≃15° with respect to the Galactic plane. A series of cavities oriented along a l ≃ 60–240° axis crosses the Arm. Conclusions . The results illustrate the ongoing synergy between 3D mapping of IS dust and stellar calibrations in the context of Gaia . Dust maps provide prior foregrounds for future calibrations appropriate to different target characteristics or ranges of extinction, allowing us in turn to increase extinction data and produce more detailed and extended maps.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.763

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.223
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it