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Thrane and C

Published notice on a work cited in the Pith corpus. Exact quotes below. No model judges whether any citation was load-bearing.

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Correction Crossref 25 open · 25 total · 0 disputed
DOI
10.1017/pasa.2019.2
Notice DOI
10.1017/pasa.2020.23
Event date
2020-09-02
Machine twin
JSON

01One-hop citing occurrences

Correction Open
Bayesian inference for compact binary coalescences with BILBY: Validation and application to the first LIGO--Virgo gravitational-wave transient catalogue

ref [162] · 2006.00714 · notice #1415 · dispute

Raw extraction · bibliography line

Thrane E., Talbot C., 2019, @doi [ ] 10.1017/pasa.2019.2 , https://ui.adsabs.harvard.edu/abs/2019PASA...36...10T 36, e010

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Thrane E., Talbot C., 2019, @doi [ ] 10.1017/pasa.2019.2, https://ui.adsabs.harvard.edu/abs/2019PASA...36...10T 36, e010

Correction Open
A practical Bayesian method for gravitational-wave ringdown analysis with multiple modes

ref [47] · 2502.01093 · notice #1420 · dispute

Raw extraction · bibliography line

Thrane, E., Talbot, C.: An introduction to Bayesian inference in gravitational-wave astronomy: parameter estimation, model selection, and hierarchical models. Publ. Astron. Soc. Austral. 36, 010 (2019) https: //doi.org/10.1017/pasa.2019.2 arXiv:1809.02293 [astro-ph.IM]. [Erratum: Publ.Astron.Soc.Austral. 37, e036 (2020)]
Correction Open
Addressing prior dependence in hierarchical Bayesian modeling for PTA data analysis II: Noise and SGWB inference through parameter decorrelation

ref [15] · 2511.01959 · notice #1417 · dispute

Raw extraction · bibliography line

An introduction to Bayesian inference in gravitational-wave as- tronomy: Parameter estimation, model selection, and hierarchical models. PASA 36, e010. doi:10.1017/pasa.2019.2,arXiv:1809.02293. Tibshirani, R., Wasserman, L.,

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An introduction to Bayesian inference in gravitational-wave as- tronomy: Parameter estimation, model selection, and hierarchical models. PASA 36, e010. doi:10.1017/pasa.2019.2,arXiv:1809.02293. Tibshirani, R., Wasserman, L

Correction Open
Precise and Rapid Parameter Inference of Kilonova with Conditional Variational Autoencoder

ref [20] · 2605.17377 · notice #1416 · dispute

Raw extraction · bibliography line

Thrane, Eric and Talbot, Colm , year=. An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models , volume=. doi:10.1017/pasa.2019.2 , journal=

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Thrane, Eric and Talbot, Colm, year=. An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models, volume=. doi:10.1017/pasa.2019.2, journal=

Correction Open
The geometry of lunar gravitational wave detection

ref [41] · 2606.04918 · notice #1426 · dispute

Raw extraction · bibliography line

Thrane, E. & Talbot, C. An introduction to bayesian inference in gravitational- wave astronomy: Parameter estimation, model selection, and hierarchical models. Publications of the Astronomical Society of Australia36, e010 (2019). URL https: //doi.org/10.1017/pasa.2019.2
Correction Open
Constraining Orbital Eccentricity of a Supermassive Black Hole Binary Candidate PKS 2131-0211

ref [34] · 2606.05343 · notice #1425 · dispute

Raw extraction · bibliography line

An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models. , keywords =. doi:10.1017/pasa.2019.2 , archivePrefix =. 1809.02293 , primaryClass =

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An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models., keywords =. doi:10.1017/pasa.2019.2, archivePrefix =. 1809.02293, primaryClass =

Correction Open
The Chirp-Mass Ladder: A New Rung Emerges

ref [1] · 2606.18081 · notice #1422 · dispute

Raw extraction · bibliography line

An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models. Publ. Astron. Soc. Aust. , keywords =. doi:10.1017/pasa.2019.2 , archivePrefix =. 1809.02293 , primaryClass =

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An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models. Publ. Astron. Soc. Aust., keywords =. doi:10.1017/pasa.2019.2, archivePrefix =. 1809.02293, primaryClass =

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