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Record W2287170194

Radio Pulsars: The Neutron Star Population Fundamental Physics

2016· preprint· en· W2287170194 on OpenAlexaff
V. M. Kaspi, M. Krämer

Bibliographic record

VenuearXiv (Cornell University) · 2016
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPulsarNeutron starPhysicsAstrophysicsAstronomyGalaxyCOSMIC cancer databaseBinary numberX-ray pulsar
DOInot available

Abstract

fetched live from OpenAlex

Radio pulsars are unique laboratories for a wide range of physics and astrophysics. Understanding how they are created, how they evolve and where we find them in the Galaxy, with or without binary companions, is highly constraining of theories of stellar and binary evolution. Pulsars' relationship with a recently discovered variety of apparently different classes of neutron stars is an interesting modern astrophysical puzzle which we consider in Part I of this review. Radio pulsars are also famous for allowing us to probe the laws of nature at a fundamental level. They act as precise cosmic clocks and, when in a binary system with a companion star, provide indispensable venues for precision tests of gravity. The different applications of radio pulsars for fundamental physics will be discussed in Part II. We finish by making mention of the newly discovered class of astrophysical objects, the Fast Radio Bursts, which may or may not be related to radio pulsars or neutron stars, but which were discovered in observations of the latter.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.053
GPT teacher head0.244
Teacher spread0.191 · 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 designTheoretical or conceptual
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
Published2016
Admission routes1
Has abstractyes

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