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PSR J1453+1902 and the radio luminosities of solitary versus binary millisecond pulsars

2007· article· en· W2053532485 on OpenAlexaff
D. R. Lorimer, M. A. McLaughlin, D. J. Champion, I. H. Stairs

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsUniversity of British ColumbiaMcGill University
Fundersnot available
KeywordsMillisecond pulsarPhysicsPulsarAstrophysicsLuminosityBinary pulsarPopulationAstronomyRadio telescopeMillisecondBinary numberProper motionTelescopeGalaxyStars

Abstract

fetched live from OpenAlex

We present 3 yr of timing observations for PSR J1453+1902, a 5.79-ms pulsar discovered during a 430-MHz drift-scan survey with the Arecibo telescope. Our observations show that PSR J1453+1902 is solitary and has a proper motion of 8 ± 2 mas yr−1. At the nominal distance of 1.2 kpc estimated from the pulsar's dispersion measure, this corresponds to a transverse speed of 46 ± 11 km s−1, typical of the millisecond pulsar population. We analyse the current sample of 55 millisecond pulsars in the Galactic disc and revisit the question of whether the luminosities of isolated millisecond pulsars are different from their binary counterparts. We demonstrate that the apparent differences in the luminosity distributions seen in samples selected from 430-MHz surveys can be explained by small-number statistics and observational selection biases. An examination of the sample from 1400-MHz surveys shows no differences in the distributions. The simplest conclusion from the current data is that the spin, kinematic, spatial and luminosity distributions of isolated and binary millisecond pulsars are consistent with a single homogeneous population.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.261
Teacher spread0.252 · 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

Citations19
Published2007
Admission routes1
Has abstractyes

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