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Paper Citation Record · LEDGER

Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2006.05919.

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

pith.paper-citation-record.v1
2006.05919 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:51:58.191931Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2d321d81-db44-45f5-af4c-f3e7eb454184 · inbound

Developing a Multi-variate Prediction Model For COVID-19 From Crowd-sourced Respiratory Voice Data cites this paper.

Developing a Multi-variate Prediction Model For COVID-19 From Crowd-sourced Respiratory Voice Data Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-24T03:53:53.867142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-24T03:53:46.500616Z digest=sha256:03b410fdf4044306ebee1e8bd38c314c692c59c0bf8aa6c3fd84dbc5e50ca83d

Observation e0a39d77-beb4-4fb2-aba7-f4ce718a1b70 · inbound

Optimising MFCC parameters for the automatic detection of respiratory diseases cites this paper.

Optimising MFCC parameters for the automatic detection of respiratory diseases Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-23T21:53:29.469333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-23T21:53:26.352337Z digest=sha256:48d3dafe231f78435608330f66cfe7ebbd904a13321d33ac72b348eaccee8625

Observation 5b15b4f2-517c-4c9e-b384-cf1fbdaa3614 · inbound

CoughViT: A Self-Supervised Vision Transformer for Cough Audio Representation Learning cites this paper.

CoughViT: A Self-Supervised Vision Transformer for Cough Audio Representation Learning Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-06T04:51:58.191931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:51:58.191931Z digest=sha256:064d500c1148e6766f3e99ff9f1442afe4fb735ccdee43faeea5653c7d4d4d2b

Observation c64761b8-7a19-4169-ac07-9889d13e7377 · inbound

CoughPhase-CLR: Designing an acoustics-informed foundation model for coughing sound classification cites this paper.

CoughPhase-CLR: Designing an acoustics-informed foundation model for coughing sound classification Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-06-26T12:59:29.477089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T12:56:07.348171Z digest=sha256:5a64f0860a3a3b07565b64444a8f0d7779a48d347bf8502235013bb586495fd1