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Record W4399911886 · doi:10.5281/zenodo.10519472

Data and Software for: 'The Radius of the High-mass Pulsar PSR J0740+6620 with 3.6 yr of NICER Data'

2024· preprint· en· W4399911886 on OpenAlexafffund
Tuomo Salmi, Devarshi Choudhury, Yves Kini, Thomas E. Riley, S. Vinciguerra, Anna L. Watts, M. T. Wolff, Zaven Arzoumanian, Slavko Bogdanov, Deepto Chakrabarty, Keith C. Gendreau, Sébastien Guillot, Wynn C. G. Ho, Daniela Huppenkothen, R. M. Ludlam, Sharon M. Morsink, Paul S. Ray

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsUniversity of Alberta
FundersAstrophysics DivisionAstrophysics Science DivisionOffice of Naval ResearchNuclear Safety and Security CommissionGoddard Space Flight CenterNatural Sciences and Engineering Research Council of CanadaSmithsonian InstitutionNederlandse Organisatie voor Wetenschappelijk OnderzoekSmithsonian Astrophysical ObservatoryCentre National d’Etudes SpatialesEuropean CommissionNational Aeronautics and Space Administration
KeywordsRADIUSPulsarPhysicsAstrophysicsQuantileCalibrationLimit (mathematics)StatisticsMathematicsComputer scienceQuantum mechanicsMathematical analysis

Abstract

fetched live from OpenAlex

Posterior sample files associated with the publication "The Radius of the High-mass Pulsar PSR J0740+6620 with 3.6 yr of NICER Data" by Salmi et al. (2024; arXiv.2406.14466; https://doi.org/10.3847/1538-4357/ad5f1f). Also included are: the data products; the numeric model files including the telescope calibration products; model modules in the Python language using the X-PSI framework; and Jupyter analysis notebooks. Please refer to the README for detailed information.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.319
Threshold uncertainty score0.971

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0030.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.3190.237

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 head0.087
GPT teacher head0.263
Teacher spread0.176 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations7
Published2024
Admission routes2
Has abstractyes

Explore more

Same venuearXiv (Cornell University)→Same topicPulsars and Gravitational Waves Research→French-language works237,207→