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Record W4315705876 · doi:10.48550/arxiv.2301.03743

LS And: WZ Sge-type outburst first time since the 1971 discovery

2023· preprint· en· W4315705876 on OpenAlexfundno aff
Taichi Kato

Bibliographic record

VenuearXiv (Cornell University) · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
FundersDeutsches Elektronen-SynchrotronStockholms UniversitetScience and Technology Facilities CouncilQueen's UniversityCalifornia Institute of TechnologyEuropean CommissionNuclear Safety and Security CommissionSpace Telescope Science InstituteNational Science FoundationUniversity of WashingtonJapan Society for the Promotion of ScienceQueen's University BelfastNational Aeronautics and Space Administration
KeywordsDwarf novaAstrophysicsPhysicsLight curveNova (rocket)Cataclysmic variable starFadingTransient (computer programming)AstronomyStarsWhite dwarfMathematicsStatisticsComputer science

Abstract

fetched live from OpenAlex

LS And was a transient discovered in 1971 in the M31 region and it has been argued whether it could be an intergalactic nova or a dwarf nova. Using the Zwicky Transient Facility (ZTF) data, I found that the object underwent the second known outburst in 2022 April. The behavior was that of a WZ Sge-type dwarf nova with a long fading tail and the light curves of the 1971 and 2022 outbursts matched very well. The light curves suggest that LS And is a typical WZ Sge-type dwarf nova near (but before reaching) the period minimum of cataclysmic variables. The true observed peak of the 1971 outburst was likely 12.2 mag. The outburst parameters were similar to those of other WZ Sge-type dwarf novae. The fading tail lasts more than a year and the object is still currently on this tail. There was a hint of 0.5-mag temporary brightening on the fading tail and the object appears still active after the outburst.

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)0.000
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.001
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 head0.066
GPT teacher head0.188
Teacher spread0.122 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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