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Record W3100617783

The NANOGrav 11 yr Data Set: Constraints on Planetary Masses Around 45 Millisecond Pulsars

2020· article· en· W3100617783 on OpenAlexaff
Erica Behrens, S. M. Ransom, Dustin R. Madison, Zaven Arzoumanian, Kathryn Crowter

Bibliographic record

VenueRepository of the Academy's Library (Library of the Hungarian Academy of Sciences) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMillisecond pulsarPulsarPhysicsAstrophysicsAstronomyData setSet (abstract data type)Computer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Abstract We search for extrasolar planets around millisecond pulsars using pulsar timing data and seek to determine the minimum detectable planetary masses as a function of orbital period. Using the 11 yr data set from the North American Nanohertz Observatory for Gravitational Waves (NANOGrav), we look for variations from our models of pulse arrival times due to the presence of exoplanets. No planets are detected around the millisecond pulsars in the NANOGrav 11 yr data set, but taking into consideration the noise levels of each pulsar and the sampling rate of our observations, we develop limits that show we are sensitive to planetary masses as low as that of the moon. We analyzed potential planet periods, P , in the range 7 days < P < 2000 days, with somewhat smaller ranges for some binary pulsars. The planetary-mass limit for our median-sensitivity pulsar within this period range is .

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.047
GPT teacher head0.304
Teacher spread0.258 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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Same venueRepository of the Academy's Library (Library of the Hungarian Academy of Sciences)Same topicPulsars and Gravitational Waves ResearchFrench-language works237,207