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Record W2087608733 · doi:10.1088/0264-9381/24/19/s28

Search method for unmodeled transient gravitational waves associated with SGR flares

2007· article· en· W2087608733 on OpenAlexfundno aff
P. Kalmus, R. Khan, L. Matone, Szabolcs Márka

Bibliographic record

VenueClassical and Quantum Gravity · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaDepartment of Science and Technology, Ministry of Science and Technology, IndiaColumbia UniversityAlexander von Humboldt-StiftungMax-Planck-GesellschaftCouncil of Scientific and Industrial Research, IndiaNational Science Foundation
KeywordsPhysicsGravitational waveDetectorWaveformTransient (computer programming)Noise (video)AstrophysicsSensitivity (control systems)SIGNAL (programming language)OpticsElectronic engineering

Abstract

fetched live from OpenAlex

We describe a method for searching for transient gravitational waves associated with soft gamma-ray repeater (SGR) flares or other burst-like events using data collected by interferometric gravitational wave detectors. The method can be used to analyze data from either a single detector or from two detectors coherently. The excess power-type algorithm creates event sets from conditioned detector data which may be compared to signal simulations of known strength based on plausible waveform classes. Estimated search sensitivities obtained by performing two-detector searches on the simulated data are presented. In the case of 22 ms duration white noise bursts in the 100–200 Hz band injected into simulated noise, we find a characteristic strain sensitivity h 90% rss = 3.0 × 10 −22 .

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.363
Teacher spread0.335 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations18
Published2007
Admission routes1
Has abstractyes

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