Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2203.06823.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T22:24:20.971690Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-17T03:18:57.226526Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation d93c3a5f-ecb7-4834-96f0-926859ff72e8 · inbound
Large-scale Multi-sequence Pretraining for Generalizable MRI Analysis in Versatile Clinical Applications cites this paper.
Large-scale Multi-sequence Pretraining for Generalizable MRI Analysis in Versatile Clinical Applications SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:24:20.971690Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46b595b1-0f57-4eeb-a993-1416342dd778 · inbound
CUTE-MRI: Conformalized Uncertainty-based framework for Time-adaptivE MRI cites this paper.
CUTE-MRI: Conformalized Uncertainty-based framework for Time-adaptivE MRI SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:24:15.672295Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a372ebc-379b-4441-94c7-1a7b21814645 · inbound
LM-CartSeg: Automated Segmentation of Lateral and Medial Cartilage and Subchondral Bone for Radiomics Analysis cites this paper.
LM-CartSeg: Automated Segmentation of Lateral and Medial Cartilage and Subchondral Bone for Radiomics Analysis SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T03:18:57.228564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.