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Record W4393815916 · doi:10.5281/zenodo.4773599

Refined Mass and Geometric Measurements of the High-Mass PSR J0740+6620: Probability Density Functions and their Credible Intervals

2021· dataset· en· W4393815916 on OpenAlexaffabout
Emmanuel Fonseca, H. Thankful Cromartie, Timothy T. Pennucci, Paul S. Ray, A. Yu. Kirichenko, S. M. Ransom, Paul B. Demorest, I. H. Stairs, Zaven Arzoumanian, L. Guillemot, A. Parthasarathy, M. Kerr, I. Cognard, P. T. Baker, Harsha Blumer, Paul R. Brook, Megan E. DeCesar, Timothy Dolch, Fengqiu Adam Dong, E. C. Ferrara, William Fiore, N. Garver-Daniels, Deborah C. Good, Ross J. Jennings, Megan L. Jones, V. M. Kaspi, Michael T. Lam, D. R. Lorimer, Jing Luo, Alexander McEwen, James W. McKee, M. A. McLaughlin, Natasha McMann, Bradley W. Meyers, Arun Naidu, Cherry Ng, David J. Nice, Nihan S. Pol, H. A. Radovan, Brent J. Shapiro-Albert, Chia Min Tan, Shriharsh P. Tendulkar, Joseph K. Swiggum, Haley M. Wahl, Weiwei Zhu

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typedataset
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of TorontoMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsStatistical physicsStatisticsPhysicsMathematics

Abstract

fetched live from OpenAlex

This Zenodo entry contains files for data used by Fonseca et al. (2021), The Astrophysical Journal Letters, 915, L12, which presents an analysis of radio-timing data for PSR J0740+6620 observed with the Green Bank Telescope and the Canadian Hydrogen Intensity Mapping Experiment telescope. See the attached README for a description of the attached data products and their use.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.036
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0360.035

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 head0.046
GPT teacher head0.271
Teacher spread0.225 · 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 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

Citations6
Published2021
Admission routes2
Has abstractyes

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