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Record W2074778956 · doi:10.1088/0004-637x/727/1/3

THE ELM SURVEY. II. TWELVE BINARY WHITE DWARF MERGER SYSTEMS

2010· article· en· W2074778956 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWhite dwarfGravitational waveSkyBinary numberBinary starNeutron starMerge (version control)Orbital period

Abstract

fetched live from OpenAlex

We describe new radial velocity and X-ray observations of extremely low-mass white dwarfs (ELM WDs, ~0.2 Msol) in the Sloan Digital Sky Survey Data Release 4 and the MMT Hypervelocity Star survey. We identify four new short period binaries, including two merger systems. These observations bring the total number of short period binary systems identified in our survey to 20. No main-sequence or neutron star companions are visible in the available optical photometry, radio, and X-ray data. Thus, the companions are most likely WDs. Twelve of these systems will merge within a Hubble time due to gravitational wave radiation. We have now tripled the number of known merging WD systems. We discuss the characteristics of this merger sample and potential links to underluminous supernovae, extreme helium stars, AM CVn systems, and other merger products. We provide new observational tests of the WD mass-period distribution and cooling models for ELM WDs. We also find evidence for a new formation channel for single low-mass WDs through binary mergers of two lower mass objects.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.010
GPT teacher head0.230
Teacher spread0.219 · 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.

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

Citations133
Published2010
Admission routes1
Has abstractyes

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