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Record W2079141294 · doi:10.1086/321733

Inferring Initial Spin Periods for Neutron Stars in Composite Remnants

2001· article· en· W2079141294 on OpenAlexaff
E. van der Swaluw, Yanqin Wu

Bibliographic record

VenueThe Astrophysical Journal · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsPhysicsSupernovaPulsarNeutron starAstrophysicsRADIUSLuminosityPulsar wind nebulaAstronomySupernova remnantMagnetarSpin (aerodynamics)NebulaStars

Abstract

fetched live from OpenAlex

We propose a method to infer the initial spin periods of pulsars residing in composite supernova remnants. Such a remnant consists of both a plerionic and a shell-type component, corresponding to the pulsar wind nebula driven by the spin-down luminosity of the central pulsar and the blast wave bounding the supernova remnant, respectively. Theoretical investigations including hydrodynamical simulations have shown that, at late times (~1000-10,000 yr), a simple scaling law connects the radius of the supernova shell to the radius of the plerion. The energy content of the plerion and the total mechanical energy of the supernova remnant enter into this scaling law. One can use this scaling law to estimate the initial spin periods of pulsars residing in composite remnants. We discuss potential pitfalls of this method, including the effect of a small remnant age and of strong radiative losses in the plerion.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.367
Teacher spread0.343 · 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 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

Citations47
Published2001
Admission routes1
Has abstractyes

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