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Record W2950067845 · doi:10.3847/1538-4357/ab2985

KSP-OT-201611a: A Distant Population II Dwarf Nova Candidate Discovered by the KMTNet Supernova Program

2019· article· en· W2950067845 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGravitational microlensingDwarf novaAccretion (finance)PopulationSupernovaWhite dwarfDwarf galaxyCataclysmic variable star

Abstract

fetched live from OpenAlex

Abstract We present a multicolor, high-cadence photometric study of a distant dwarf nova KSP-OT-201611a discovered by the Korea Microlensing Telescope Network Supernova Program. From 2016 October to 2017 May, two outbursts, which comprise a super/long outburst followed by a normal/short outburst separated by ∼91 days, were detected in the BVI bands. The shapes and amplitudes of the outbursts reveal the nature of KSP-OT-201611a to be an SU UMa- or U Gem-type dwarf nova. Color variations of periodic humps in the super/long outburst possibly indicate that KSP-OT-201611a is an SU UMa-type dwarf nova. The super and normal outbursts show distinctively different color evolutions during the outbursts due most likely to the difference in time when the cooling wave is formed in the accretion disk. The outburst peak magnitudes and the orbital period of the dwarf nova indicate that it is at a large Galactocentric distance (∼13.8 kpc) and height (∼1.7 kpc) from the Galactic plane. KSP-OT-201611a, therefore, may provide a rare opportunity to study the accretion disk process of Population II dwarf novae.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.009
GPT teacher head0.243
Teacher spread0.234 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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