Paper Citation Record · LEDGER

Hierarchies of Calibration: Classification meets Regression

As of 14 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2606.03245.

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

pith.paper-citation-record.v1
2606.03245 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T08:23:08.359288Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

verified exact2
verified fuzzy0
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 77447ebc-6c52-4f26-84a2-34a3a253c500 · outbound

This paper cites In-sample calibration yields conformal calibration guarantees.

Hierarchies of Calibration: Classification meets Regression In-sample calibration yields conformal calibration guarantees

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T05:16:39.400700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4946bc3d-dbb3-44cf-8e00-2cf31add5580 · outbound

This paper cites Three Types of Calibration with Properties and their Semantic and Formal Relationships.

Hierarchies of Calibration: Classification meets Regression Three Types of Calibration with Properties and their Semantic and Formal Relationships

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:16:39.400302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9c90705b-3a75-48de-9db9-b508465efef2 · outbound

This paper cites E., Westveld III, A.

Hierarchies of Calibration: Classification meets Regression E., Westveld III, A

Reference 3

Resolution: verified exact; doi, observed 2026-06-28T10:32:00.913815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 72a02f00-0e5e-422c-8a30-a142a15fea2d · outbound

This paper cites Analogously, we obtainG(F −1 + (α)−) = 0 forα < f(1) andG(F −1 + (α)−) =g(1) otherwise.

Hierarchies of Calibration: Classification meets Regression Analogously, we obtainG(F −1 + (α)−) = 0 forα < f(1) andG(F −1 + (α)−) =g(1) otherwise

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T08:23:08.359288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b6dd2b5-65ad-4230-9c52-a55045c6a7af · outbound

This paper cites Case NC = PC: As a direct consequence of the preceding observation,Fis probabilistically calibrated forYif, and only if,F ρ is probabilistically calibrated forY ρ.

Hierarchies of Calibration: Classification meets Regression Case NC = PC: As a direct consequence of the preceding observation,Fis probabilistically calibrated forYif, and only if,F ρ is probabilistically calibrated forY ρ

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T08:23:08.359288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fdf3c64-892e-48c3-b1e9-d3075d1f1095 · outbound

This paper cites (2019, Supplement, Table.

Hierarchies of Calibration: Classification meets Regression (2019, Supplement, Table

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T08:23:08.359288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ced61ae-3f5c-43aa-bdf4-b0cb389e11e9 · outbound

This paper cites (2023, Footnote.

Hierarchies of Calibration: Classification meets Regression (2023, Footnote

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T08:23:08.359288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2458aaf3-486d-49d2-818b-c2776c46ac20 · outbound

This paper cites Therefore, EY∼Q [S(x, Y)−S(t, Y)] = Z [S(x, y)−S(t, y)]dQ(y) = Z Z [S(x, y)−S(t, y)]dP(y)dΛ(P) = Z EY∼P [S(x, Y)−S(t, Y)]dΛ(P) ( = 0,ifx∈s, >0,otherwise.

Hierarchies of Calibration: Classification meets Regression Therefore, EY∼Q [S(x, Y)−S(t, Y)] = Z [S(x, y)−S(t, y)]dQ(y) = Z Z [S(x, y)−S(t, y)]dP(y)dΛ(P) = Z EY∼P [S(x, Y)−S(t, Y)]dΛ(P) ( = 0,ifx∈s, >0,otherwise

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T08:23:08.359288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3430613b-730f-4a86-bcae-7adae5bd2410 · outbound

This paper cites an unresolved cited work.

Hierarchies of Calibration: Classification meets Regression Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T08:23:08.359288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fb5dcbc-cab6-46e4-8174-98fb1f55870b · outbound

This paper cites •The claims for Example 2.2 in Tables 2, 3, and.

Hierarchies of Calibration: Classification meets Regression •The claims for Example 2.2 in Tables 2, 3, and

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T08:23:08.359288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c4d8d78-32a9-4dc5-92a8-ec508cf2c510 · outbound

This paper cites 33 We now explain how we ensure calibration properties by construction, taking Example 2.4 (b) from Gneiting and Resin (2023) as a blue print.

Hierarchies of Calibration: Classification meets Regression 33 We now explain how we ensure calibration properties by construction, taking Example 2.4 (b) from Gneiting and Resin (2023) as a blue print

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T08:23:08.359288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c72c6f69-fb73-4e8b-a3b5-ca6440116e00 · outbound

This paper cites Finally, we verify the claims about the quantile-based notions QC and UQC in Table B.1.

Hierarchies of Calibration: Classification meets Regression Finally, we verify the claims about the quantile-based notions QC and UQC in Table B.1

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T08:23:08.359288Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.