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On the triple peaks of SNHunt248 in NGC 5806

2015· article· en· W6922157514 on OpenAlexfundno aff

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsnot available
FundersComisión Nacional de Investigación Científica y TecnológicaScience and Technology Facilities CouncilPlanetary Science DivisionScience Mission DirectorateSmithsonian Astrophysical ObservatoryMax-Planck-Institut für AstronomieQueen's UniversityEötvös Loránd TudományegyetemEuropean CommissionJohns Hopkins UniversityQueen's University BelfastNational Aeronautics and Space AdministrationNational Central UniversitySpace Telescope Science InstituteDurham UniversitySmithsonian InstitutionNational Science Foundation
KeywordsAbsolute magnitudeLight curveLuminosityBlack-body radiationSupernovaMagnitude (astronomy)EjectaSpectral energy distributionApparent magnitude

Abstract

fetched live from OpenAlex

We present our findings on a supernova (SN) impostor, SNHunt248, based on optical and near-IR data spanning ~15 yr before discovery, to ~1 yr post-discovery. The light curve displays three distinct peaks, the brightest of which is at MR ~ −15.0 mag. The post-discovery evolution is consistent with the ejecta from the outburst interacting with two distinct regions of circumstellar material. The 0.5–2.2 μm spectral energy distribution at −740 d is well-matched by a single 6700 K blackbody with log (L/L⊙) ~ 6.1. This temperature and luminosity support previous suggestions of a yellow hypergiant progenitor; however, we find it to be brighter than the brightest and most massive Galactic late-F to early-G spectral type hypergiants. Overall the historical light curve displays variability of up to ~ ± 1 mag. At current epochs (~1 yr post-outburst), the absolute magnitude (MR ~ − 9 mag) is just below the faintest observed historical absolute magnitude ~10 yr before discovery.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.222
Teacher spread0.203 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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