Pith Number

pith:B3DHQNC2

pith:2025:B3DHQNC2SEESLDVDTEDZQU6R2Q

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Bayesian Methods for the Investigation of Temperature-Dependence in Conductivity

Andrew R. McCluskey, Benjamin J. Morgan, Samuel W. Coles

Bayesian methods provide a coherent framework to fit models like Arrhenius to temperature-dependent conductivity data while quantifying uncertainties and enabling extrapolation.

arxiv:2512.17792 v5 · 2025-12-19 · cond-mat.mtrl-sci

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Record completeness

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4 Citations open

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Claims

C1strongest claim

Bayesian methods offer a coherent framework that addresses quantifying the uncertainty of fitted parameters, assessing whether the data quality is sufficient to support a particular empirical model, and using these models to predict behaviour at temperatures outside the measured range.

C2weakest assumption

That the empirical models (e.g., Arrhenius) are appropriate descriptions of the underlying temperature dependence and that the chosen priors and likelihoods are suitable for the data; if the model form is misspecified, model selection and extrapolation lose validity.

C3one line summary

Bayesian inference provides a framework for parameter estimation, model selection, and uncertainty-aware extrapolation when analyzing temperature-dependent ionic conductivity and diffusion data.

Formal links

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Receipt and verification

First computed	2026-05-25T02:01:11.089528Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

0ec678345a9109258ea399079853d1d407f8db96ed7756ccc5247274414c40e4

Aliases

arxiv: 2512.17792 · arxiv_version: 2512.17792v5 · doi: 10.48550/arxiv.2512.17792 · pith_short_12: B3DHQNC2SEES · pith_short_16: B3DHQNC2SEESLDVD · pith_short_8: B3DHQNC2

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/B3DHQNC2SEESLDVDTEDZQU6R2Q \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 0ec678345a9109258ea399079853d1d407f8db96ed7756ccc5247274414c40e4

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "be908e9c9861bde94a3f9895db2a0ab833391130c1a90ee5cb6bd588fc4b9dae",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cond-mat.mtrl-sci",
    "submitted_at": "2025-12-19T16:59:38Z",
    "title_canon_sha256": "83303005463d934fe25cb9020513c88e0003ea1437a00fc32f24eb9f89948476"
  },
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  "source": {
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    "kind": "arxiv",
    "version": 5
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}