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Record W2775108260 · doi:10.3847/1538-3881/aab9be

Revised Distances to 21 Supernova Remnants

2018· article· en· W2775108260 on OpenAlexaff
S. Ranasinghe, D. A. Leahy

Bibliographic record

VenueThe Astronomical Journal · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSupernovaAstrophysicsPhysicsSkyGalactic planeLine (geometry)Supernova remnantGalaxy rotation curveAstronomyRotation (mathematics)KinematicsGalaxyGeometryMathematicsGalaxy formation and evolution

Abstract

fetched live from OpenAlex

Abstract We carry out a comprehensive study of Hi21 cm line observations and13CO line observations of 21 supernova remnants (SNRs). The aim of the study is to search for Hiabsorption features to obtain kinematic distances in a consistent manner. The 21 SNRs are in the region of sky covered by the Very Large Array Galactic Plane Survey (Hi21 cm observations) and Galactic Ring Survey (13CO line observations). We obtain revised distances for 10 SNRs based on new evidence in the Hiand13CO observations. We revise distances for the other 11 SNRs based on an updated rotation curve and new error analysis. The mean change in distance for the 21 SNRs is ≃25%, i.e., a change of 1.5 kpc compared to a mean distance for the sample of 6.4 kpc. This has a significant impact on interpretation of the physical state of these SNRs. For example, using a Sedov model, age and explosion energy scale as the square of distance, and inferred ISM density scales as distance.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations67
Published2018
Admission routes1
Has abstractyes

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