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What do we know about cosmography

Cosmology and Nongalactic Astrophysics · Submitted 8 Jan 2016

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Minimizing risk, it suggests that cosmography up to the second order is the best approximation.

how it is stated · hedged possibility 0.97 read the record →

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arXiv ID1601.01758 (version 2)
Pith IDQLDVSWEI, Pith's permanent record of this paper and its review
CitationHong Li, Jun-Qing Xia, Ming-Jian Zhang. "What do we know about cosmography." arXiv:1601.01758 (2016). https://pith.science/paper/QLDVSWEI
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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 6,795 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.89 · human participants 0.01 · controlled comparison 0.05 · randomized assignment 0.01 · states quantitative result 0.22 · compares with prior results 0.27 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; .

In the present paper, we investigate the cosmographic problem using the bias-variance trade-off. We find that both the z-redshift and the $y=z/(1+z)$-redshift can present a small bias estimation. It means that the cosmography can describe the supernova data more accurately. Minimizing risk, it suggests that cosmography up to the second order is the best approximation. Forecasting the constraint from future measurements, we find that future supernova and redshift drift can significantly improve the constraint, thus having the potential to solve the cosmographic problem. We also exploit the values of cosmography on the deceleration parameter and equation of state of dark energy $w(z)$. We find that supernova cosmography cannot give stable estimations on them. However, much useful information was obtained, such as that the cosmography favors a complicated dark energy with varying $w(z)$, and the derivative $dw/dz<0$ for low redshift. The cosmography is helpful to model the dark energy.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 In the present paper, we investigate the cosmographic problem using the bias-variance trade-off. contribution 0.93 0.89 0.04 asserted 0.89
s1 We find that both the z-redshift and the $y=z/(1+z)$-redshift can present a small bias estimation. result 1.00 0.95 0.11 asserted 0.71
s2 It means that the cosmography can describe the supernova data more accurately. interpretation 0.98 0.71 0.16 asserted 0.95
s3 Minimizing risk, it suggests that cosmography up to the second order is the best approximation. result 0.65 0.84 0.37 hedged possibility 0.97
s4 Forecasting the constraint from future measurements, we find that future supernova and redshift drift can significantly improve the constraint, thus having the potential to solve the cosmographic problem. result 0.77 0.92 0.23 asserted 0.59
s5 We also exploit the values of cosmography on the deceleration parameter and equation of state of dark energy $w(z)$. contribution 0.75 0.86 0.04 asserted 0.88
s6 We find that supernova cosmography cannot give stable estimations on them. result 0.76 0.92 0.10 asserted 1.00
s7 However, much useful information was obtained, such as that the cosmography favors a complicated dark energy with varying $w(z)$, and the derivative $dw/dz<0$ for low redshift. result 0.84 0.89 0.14 asserted 0.84
s8 The cosmography is helpful to model the dark energy. interpretation 0.96 0.45 0.14 asserted 0.97

What kind of paper the classifier reports this is: theoretical result 0.58 · evidence from analysis of existing data 0.92.

What was examined, and what was not

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

In the present paper, we investigate the cosmographic problem using the bias-variance trade-off. We find that both the z-redshift and the $y=z/(1+z)$-redshift can present a small bias estimation. It means that the cosmography can describe the supernova data more accurately. Minimizing risk, it suggests that cosmography up to the second order is the best approximation. Forecasting the constraint from future measurements, we find that future supernova and redshift drift can significantly improve the constraint, thus having the potential to solve the cosmographic problem. We also exploit the values of cosmography on the deceleration parameter and equation of state of dark energy $w(z)$. We find that supernova cosmography cannot give stable estimations on them. However, much useful information was obtained, such as that the cosmography favors a complicated dark energy with varying $w(z)$, and the derivative $dw/dz<0$ for low redshift. The cosmography is helpful to model the dark energy.

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References
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15 arXiv papers cite this in 20 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

Papers citing it · 16 sentences without a confident label

Cites it as background 4 papers

What it cites · 2 sentences without a confident label

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