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Record W4297916267 · doi:10.48550/arxiv.2109.05044

Evaluating and Enhancing Candidate Clocking Systems for CHIME/FRB VLBI\n Outriggers

2021· preprint· en· W4297916267 on OpenAlexaboutno aff
Savannah Cary, Juan Mena-Parra, Calvin Leung, Kiyoshi W. Masui, Jane Kaczmarek, Tomás Cassanelli

Bibliographic record

VenuearXiv (Cornell University) · 2021
Typepreprint
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsnot available
Fundersnot available
KeywordsVery-long-baseline interferometryOutriggerHydrogen maserMaserComputer sciencePhysicsGeodesyAstronomyGeology

Abstract

fetched live from OpenAlex

As the Canadian Hydrogen Intensity Mapping Experiment (CHIME) has become the\nleading instrument for detecting Fast Radio Bursts (FRBs), CHIME/FRB Outriggers\nwill use very-long-baseline interferometry (VLBI) to localize FRBs with\nmilliarcsecond precision. The CHIME site uses a passive hydrogen maser\nfrequency standard in order to minimize localization errors due to clock delay.\nHowever, not all outrigger stations will have access to a maser. This report\npresents techniques used to evaluate clocks for use at outrigger sites without\na maser. More importantly, the resulting algorithm provides calibration methods\nfor clocks that do not initially meet the stability requirements for VLBI, thus\nallowing CHIME/FRB Outriggers to remain true to the goal of having\nmilliarcsecond precision.\n

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.081
GPT teacher head0.217
Teacher spread0.136 · 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 designSimulation or modeling
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
Published2021
Admission routes1
Has abstractyes

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