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Paper Citation Record · LEDGER

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework

As of 17 August 2026, this Paper Citation Record lists 100 of 169 outbound references and 1 inbound Pith citation observation for arXiv:2502.10037.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.10037 v2

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measured 100 of 169 reference resolution

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Outbound references

Observation c95d2387-109e-46aa-b385-c34ebc298ec8 · outbound

This paper cites an unresolved cited work.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework Unresolved cited work

Reference 1

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This paper cites 2024a, JCAP, 12, 055 https://doi.org/10.1088/1475-7516/2024/12/055.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2024a, JCAP, 12, 055 https://doi.org/10.1088/1475-7516/2024/12/055

Reference 2

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This paper cites Dark energy constraints using gamma-ray burst correlations with DESI 2024 data.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework Dark energy constraints using gamma-ray burst correlations with DESI 2024 data

Reference 3

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This paper cites 2024c, JHEAP, 42, 178 https://doi.org/10.1016/j.jheap.2024.05.002.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2024c, JHEAP, 42, 178 https://doi.org/10.1016/j.jheap.2024.05.002

Reference 4

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This paper cites https://doi.org/10.1093/mnrasl/slz056 2019, MNRAS, 486, L46.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework https://doi.org/10.1093/mnrasl/slz056 2019, MNRAS, 486, L46

Reference 5

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This paper cites https://doi.org/10.1051/0004-6361:20020722 2002, A&A, 390, 81.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework https://doi.org/10.1051/0004-6361:20020722 2002, A&A, 390, 81

Reference 6

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This paper cites 2008, MNRAS, 391, 577 https://doi.org/10.1111/j.1365-2966.2008.13943.x.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2008, MNRAS, 391, 577 https://doi.org/10.1111/j.1365-2966.2008.13943.x

Reference 7

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This paper cites & Della Valle 2013, IJMPD, 22, 1330028 https://10.1142/S0218271813300280.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework & Della Valle 2013, IJMPD, 22, 1330028 https://10.1142/S0218271813300280

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This paper cites G., & Hernandez, X.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework G., & Hernandez, X

Reference 9

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This paper cites C., Clarkson, C., & Seikel, M.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework C., Clarkson, C., & Seikel, M

Reference 10

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework Unresolved cited work

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This paper cites G., Cordier, B.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework G., Cordier, B

Reference 12

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework & Cimatti, A

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework Unresolved cited work

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This paper cites 2022a, MNRAS, 512, 439 https://doi.org/10.1093/mnras/stac517.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2022a, MNRAS, 512, 439 https://doi.org/10.1093/mnras/stac517

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework G., & Ratra, B

Reference 16

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework Unresolved cited work

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework & Ratra, B

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2008, A&A, 490, 31 https://doi.org/10.1051/0004-6361:200810337

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework & Izzo, L

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2010, A&A, 519, A73 https://doi.org/10.1051/0004-6361/201014522

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This paper cites 2018, MNRAS, 476, 3924 https://doi.org/10.1093/mnras/sty422.

Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2018, MNRAS, 476, 3924 https://doi.org/10.1093/mnras/sty422

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework F., Capozziello, S., & Dainotti, M

Reference 23

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework F., Zhang, T

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework & Polarski, D

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework B., et al

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework Fits, and especially linear fits, with errors on both axes, extra variance of the data points and other complications

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework G., Postnikov, S., & Hernandez, X

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework G., & Amati, L., https://doi.org/10.1088/1538-3873/aaa8d7 2018, PASP, 130, 051001

Reference 31

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework G., et al

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework G., De Simone B., Schiavone T., et al., 2021, ApJ, 912, 150 https://doi.org/10.3847/1538-4357/abeb73

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework A New Master Supernovae Ia sample and the investigation of the $H_0$ tension

Reference 34

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework G., & Amati, L.,

Reference 35

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework G., et al

Reference 36

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2004, ApJ, 612, L101 https://doi.org/10.1086/424694

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Observation 29762fa5-9d26-4058-8a65-dd22e3dfb10a · outbound

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2022, JCAP, 04, 016 https://doi.org/10.1088/1475-7516/2022/04/016

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Observation dc297071-0933-48f9-934c-c7e476f4abda · outbound

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2005, MNRAS, 360, L1 https://doi.org/10.1111/j.1745-3933.2005.00023.x

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Observation 7c0c4629-1f80-4dbe-9214-e2c5fa490f1d · outbound

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2012, IJMPD, 21, 1250016 https://doi.org/10.1142/S0218271812500162

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2004a, ApJ, 616, 331 https://doi.org/10.1086/424913

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2004b, ApJ, 613, L13 https://doi.org/10.1086/424915

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2024, EPJC, 84, 934 https://doi.org/10.1140/epjc/s10052-024-13304-5

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2015, A&A, 582, A115 https://doi.org/10.1051/0004-6361/201526461

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Observation 0bd804c2-2ef3-41b9-8fa7-dca633b70f28 · outbound

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Observation c8710f64-f82c-4c2e-a56a-15ab9cd9c393 · outbound

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Gamma-Ray Bursts Calibrated from the Observational $H(z)$ Data in Artificial Neural Network Framework 2003, PRL, 90, 091301 https://doi.org/10.1103/PhysRevLett.90.091301

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Observation ab81a79b-8347-4040-a071-055b754b6905 · inbound

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