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Record W2964276589 · doi:10.22323/1.215.0047

Pulsars in Globular Clusters with the SKA

2015· article· en· W2964276589 on OpenAlexaff
J. W. T. Hessels, Andrea Possenti, M. Bailes, C. Bassa, P. C. C. Freire, D. R. Lorimer, Ryan S. Lynch, S. M. Ransom, I. H. Stairs

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsGlobular clusterPulsarMillisecond pulsarPhysicsAstrophysicsAstronomyObservablePopulationSkyCluster (spacecraft)StarsComputer science

Abstract

fetched live from OpenAlex

Globular clusters are highly efficient radio pulsar factories. These pulsars can be used as precision probes of the clusters' structure, gas content, magnetic field, and formation history; some of them are also highly interesting in their own right because they probe exotic stellar evolution scenarios as well as the physics of dense matter, accretion, and gravity. Deep searches with SKA1-MID and SKA1-LOW will plausibly double to triple the known population. Such searches will only require one to a few tied-array beams, and can be done during early commissioning of the telescopebefore an all-sky pulsar survey using hundreds to thousands of tied-array beams is feasible. With SKA2 it will be possible to observe most of the active radio pulsars within a large fraction of the Galactic globular clusters, an estimated population of 600 -3700 observable pulsars (those beamed towards us). This rivals the total population of millisecond pulsars that can be found in the Galactic field; fully characterizing it will provide the best-possible physical laboratories as well as a rich dynamical history of the Galactic globular cluster system.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.147

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 head0.013
GPT teacher head0.215
Teacher spread0.203 · 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.

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

Citations14
Published2015
Admission routes1
Has abstractyes

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