MétaCan
Menu
Back to cohort
Record W2315421110 · doi:10.1093/mnras/stu774

A hyperspectral view of Cassiopeia A

2014· article· en· W2315421110 on OpenAlexaff
Alexandre Alarie, Antoine Bilodeau, Laurent Drissen

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversité LavalCentre for Research in Astrophysics of Québec
Fundersnot available
KeywordsPhysicsAstrophysicsCassiopeia ASupernova remnantRadial velocityProper motionSpectral lineSpectral resolutionAstronomySupernovaStars

Abstract

fetched live from OpenAlex

We used the imaging Fourier transform spectrometer Spectromètre Imageur de l'Observatoire du Mont-Mégantic (SpIOMM) to obtain hyperspectral cubes of the young supernova remnant Cassiopeia A (Cas A). The cubes contain over 5000 spatially resolved spectra covering the spectral range 6480–7050 Å. We first investigate the slow-moving N-rich quasi-stationary flocculi by measuring their radial velocity as well as the [N ii] λ6583/Hα ratio. No correlation between their radial velocity and [N ii] λ6583/Hα ratio with their location has been found. We used multi-epoch observations from the Hubble Space Telescope to create a proper motion map, showing the displacement of several filaments over the most part of Cas A. Combining data from SpIOMM and Hubble, we re-evaluate the distance to Cas A and obtained 3.33 ± 0.10 kpc, which is in good agreement with previous estimates. Finally, we obtain a three-dimensional spatial view of the [S ii] λλ6716, 6731 emissions showing their location, expansion velocity and the [S ii] doublet line ratio for multiple locations in the remnant. The velocity asymmetry reported by previous analyses is clearly visible. Also, the [S ii] doublet ratio (with a mean value of 0.5 ± 0.2) indicates a very high and variable electronic density throughout the remnant.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.006
GPT teacher head0.197
Teacher spread0.191 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations50
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueMonthly Notices of the Royal Astronomical SocietySame topicAstrophysics and Cosmic PhenomenaFrench-language works237,207