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Record W2905312720 · doi:10.3847/1538-4357/aaf886

Constraining the Magnetic Field of the Smith High-velocity Cloud Using Faraday Rotation

2019· article· en· W2905312720 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of TorontoDominion Astrophysical ObservatoryUniversity of British Columbia
Fundersnot available
KeywordsMagnetic fieldFaraday effectMilky WayMeasure (data warehouse)Field (mathematics)Rotation (mathematics)L-shellMagnetic cloud

Abstract

fetched live from OpenAlex

Abstract The Smith Cloud is a high-velocity cloud with an orbit suggesting it has made at least one passage through the Milky Way disk. A magnetic field found around this cloud has been thought to provide extra stability as it passes through the Galactic halo. We use the Karl G. Jansky Very Large Array to measure Faraday rotation measures (RMs) toward 1105 extragalactic background point sources behind and next to the Smith Cloud to constrain the detailed geometry and strength of its magnetic field. The RM pattern across the cloud gives the detailed morphology of the magnetic field structure, which indicates a field draped over the ionized gas and compressed at the head of the cloud. We constrain the peak line-of-sight magnetic field strength to ≳+5 μG and create a model of the magnetic field to demonstrate that a draped configuration can qualitatively explain the morphology of the observed RMs.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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

Citations28
Published2019
Admission routes1
Has abstractyes

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