MétaCan
Menu
Back to cohort
Record W4398805277 · doi:10.7910/dvn/qfcbcl

Simulated Noisy BBH Merger Signals and Spectrograms for: A Complex Window-Based Joint-Chirp-Rate-Time-Frequency Transform for BBH Merger Gravitational Wave Signal

2023· dataset· en· W4398805277 on OpenAlex
Xiyuan Li

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHarvard Dataverse · 2023
Typedataset
Languageen
FieldPhysics and Astronomy
TopicAdvanced Frequency and Time Standards
Canadian institutionsWestern University
Fundersnot available
KeywordsSpectrogramChirpSIGNAL (programming language)Joint (building)AcousticsGravitational waveWindow (computing)PhysicsComputer scienceSpeech recognitionOpticsEngineeringAstrophysics

Abstract

fetched live from OpenAlex

Part 1): Simulated Binary Black Hole (BBH) merger waveforms (frequency-domain IMRPhenomD Model) with advanced LIGO detector characteristic noise. - M1200 Dataset: 12,500 noisy merger time-series waveforms from distances 600 - 1200 Mpc; 12,500 aLIGO detector noise time-series waveforms. - M2000 Dataset: 12,500 noisy merger time-series waveforms from distances 1400- 2000 Mpc; 12,500 aLIGO detector noise time-series waveforms. Part 2): JCTFT and QT spectrograms of M1200 and M2000 time-series data. - JCTFT M1200 Dataset - JCTFT M2000 Dataset - QT M1200 Dataset - QT M2000 Dataset

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.019
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.004

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 head0.030
GPT teacher head0.277
Teacher spread0.248 · 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