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Paper Citation Record · LEDGER

Multi-Source COVID-19 Detection via Variance Risk Extrapolation

As of 18 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2506.23208.

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

pith.paper-citation-record.v1
2506.23208 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:51:42.192808Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T09:42:05.906583Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T09:45:23.378493Z

Reference resolution

18 of 18 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e1c78704-c64d-4baf-a1da-b1171390b757 · outbound

This paper cites A large imaging database and novel deep neural ar- chitecture for covid-19 diagnosis.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation A large imaging database and novel deep neural ar- chitecture for covid-19 diagnosis

Reference 1

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unresolved
no resolver link, observed 2026-08-06T21:51:39.839099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:39.839099Z digest=sha256:8a82cb4a87c60a84eb8b776e1872783cfacfb2a5ddb0a68e9cd037edbb30290e

Observation 0719b5fc-ad5c-4829-be65-d0010d06b272 · outbound

This paper cites Data-driven covid-19 detection through medical imaging.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Data-driven covid-19 detection through medical imaging

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:39.958914Z digest=sha256:876053939b0fe8d183ef586184bbf271b2c06bc82b981222102b0ad326d774d8

Observation e164bd17-a619-454d-9d11-30b015f93531 · outbound

This paper cites Covid- 19 computer-aided diagnosis through ai-assisted ct imaging analysis: Deploying a medical ai system.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Covid- 19 computer-aided diagnosis through ai-assisted ct imaging analysis: Deploying a medical ai system

Reference 3

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no resolver link, observed 2026-08-06T21:51:40.147036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:40.147036Z digest=sha256:03b9fe1b919489e0a4ccf84e83c3ab320a376ed51bd02c6d48f04e175d9eb2ae

Observation 27f2045a-f630-4b74-bab9-b0e4b6818530 · outbound

This paper cites Cmc-cov19d: Contrastive mixup classification for covid-19 diagnosis.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Cmc-cov19d: Contrastive mixup classification for covid-19 diagnosis

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-06T21:51:43.057920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:51:40.324992Z digest=sha256:3167af37b86b778a6d0eabe106c012572d301139613ecfd7b1b42c47dd450c25

Observation 5e033624-9d11-4a8b-83d9-df8043349dc9 · outbound

This paper cites Periphery-aware covid-19 diagnosis with contrastive repre- sentation enhancement.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Periphery-aware covid-19 diagnosis with contrastive repre- sentation enhancement

Reference 5

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no resolver link, observed 2026-08-06T21:51:40.476494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:40.476494Z digest=sha256:421e7bae941d114c23c915daf2c87d621f81466b16773f9c93d1717383359eb3

Observation a26c8c84-9966-4a39-abff-31ebcad9e250 · outbound

This paper cites Cmc v2: Towards more accu- rate covid-19 detection with discriminative video priors.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Cmc v2: Towards more accu- rate covid-19 detection with discriminative video priors

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:51:42.798744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:51:40.606446Z digest=sha256:424b2dc3d9ba0f31aee94e4c6628326a25cf946b97a25dc78d6dfedec073f5b1

Observation ec4d4bf7-8788-47a5-9afc-01b696a357bc · outbound

This paper cites Boosting covid-19 severity detec- tion with infection-aware contrastive mixup classification.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Boosting covid-19 severity detec- tion with infection-aware contrastive mixup classification

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-06T21:51:42.587698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:51:40.792169Z digest=sha256:e76da62e9416638f8ce2ab1b885e056b73cd16ee337e4a3509463eb33fabe556

Observation 29e127eb-b373-4701-8a61-3e19c63e2ee6 · outbound

This paper cites Deep neural archi- tectures for prediction in healthcare.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Deep neural archi- tectures for prediction in healthcare

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:40.931155Z digest=sha256:5f7a32708622606db64f0f3ebd250dddce392db024467879df71e7187ab61ea4

Observation dbc138d9-cb41-4cbb-a7b7-2ead40970356 · outbound

This paper cites Deep Transparent Prediction through Latent Representation Analysis.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Deep Transparent Prediction through Latent Representation Analysis

Reference 9

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no resolver link, observed 2026-08-06T21:51:41.075920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:41.075920Z digest=sha256:d03400ef3be747fd6de5a8ce6d6ec427599768948bf1107071ef2bfddc29457d

Observation a458f7d6-5887-4b2b-902c-c67228bfd07d · outbound

This paper cites Transpar- ent adaptation in deep medical image diagnosis.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Transpar- ent adaptation in deep medical image diagnosis

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:41.210301Z digest=sha256:fa403627c86fa4581c9958d6cfc5ddf884b983733b074c6207f7280cc738b0ea

Observation 605364ab-062b-4386-a633-1494e6cbc11e · outbound

This paper cites Mia-cov19d: Covid-19 detection through 3-d chest ct image analysis.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Mia-cov19d: Covid-19 detection through 3-d chest ct image analysis

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:41.376676Z digest=sha256:a0ef33beb975cd4ec57032a0df6914b0552439b487ac3cbf3896e8715af77e47

Observation 51dbe63a-dc7f-40f4-885a-41f20dbdea86 · outbound

This paper cites Ai-mia: Covid-19 detection and severity analysis through medical imaging.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Ai-mia: Covid-19 detection and severity analysis through medical imaging

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T21:51:41.548413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:41.548413Z digest=sha256:4e13c4513644c235d922211e3bad764e669d03b2ed78658851eb2c97e3ae80af

Observation 926fc845-1043-49fd-a9e6-2e8ef750237f · outbound

This paper cites Ai-enabled analysis of 3-d ct scans for diagnosis of covid-19 & its severity.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Ai-enabled analysis of 3-d ct scans for diagnosis of covid-19 & its severity

Reference 13

Resolution
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no resolver link, observed 2026-08-06T21:51:41.677959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:41.677959Z digest=sha256:917619942cd6817ff058b1a11e630e784bf90f673ac9f7ce716ce44f645eb09c

Observation 22ab747c-7491-426d-a7f9-ac1c394feaec · outbound

This paper cites A deep neural architecture for harmonizing 3-d input data analysis and decision making in medical imaging.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation A deep neural architecture for harmonizing 3-d input data analysis and decision making in medical imaging

Reference 14

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no resolver link, observed 2026-08-06T21:51:41.790820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:41.790820Z digest=sha256:4745faafb5b2c7f33920413c4bdc6f52eab8af38ba9d08ac211cf135a8a2e334

Observation eb8d6aa3-b94a-4deb-8661-b5c57430e5a7 · outbound

This paper cites Domain adaptation explainability & fairness in ai for medical image analysis: Diagnosis of covid-19 based on 3-d chest ct-scans.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Domain adaptation explainability & fairness in ai for medical image analysis: Diagnosis of covid-19 based on 3-d chest ct-scans

Reference 15

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no resolver link, observed 2026-08-06T21:51:41.912062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:41.912062Z digest=sha256:2fec80893606af6ce8904834096c90db5d574643e018772e9284fed5b76eb37a

Observation 40c400b9-61b7-467b-8b94-751380425c1f · outbound

This paper cites SAM2CLIP2SAM: Vision Language Model for Segmentation of 3D CT Scans for Covid-19 Detection.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation SAM2CLIP2SAM: Vision Language Model for Segmentation of 3D CT Scans for Covid-19 Detection

Reference 16

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no resolver link, observed 2026-08-06T21:51:42.053095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:42.053095Z digest=sha256:067b2c0a0a5dd62a98b1015adea9b1d90b3b4be4cad16f1a5eba765c47afdf00

Observation 191a223d-3644-4c3d-a3d8-1496708b7b70 · outbound

This paper cites Out-of-distribution general- ization via risk extrapolation (rex).

Multi-Source COVID-19 Detection via Variance Risk Extrapolation Out-of-distribution general- ization via risk extrapolation (rex)

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:51:42.382312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:51:42.137383Z digest=sha256:5ffcc44500876a66f4edb538cbf4ee5853855ed3526e0cc104a151c2e0a72abd

Observation 14bfe113-3dd2-453c-ae41-27e3f517f61b · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Multi-Source COVID-19 Detection via Variance Risk Extrapolation mixup: Beyond Empirical Risk Minimization

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:42.192808Z digest=sha256:86de0faed07193356d9c532ee6ba8411943423368b68c5c4f260cca4c34b8af8

Pith citing papers

Observation b0708898-862a-47e3-bf69-857b79639c56 · inbound

Towards Fair and Robust Volumetric CT Classification via KL-Regularised Group Distributionally Robust Optimisation cites this paper.

Towards Fair and Robust Volumetric CT Classification via KL-Regularised Group Distributionally Robust Optimisation Multi-Source COVID-19 Detection via Variance Risk Extrapolation

Reference 27

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arxiv_id, observed 2026-05-15T09:45:23.381828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-15T09:42:05.906583Z digest=sha256:10584f19ca87d2b41e11c86eb0a1e5e3a699d43bda166748eaccd7dc2e2ac261