Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fairness-enhancing mixed effects deep learning improves fairness on in- and out-of-distribution clustered (non-iid) data
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2310.03146.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:35:04.055153Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T21:16:38.323486Z
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 8f8433c3-b226-4b64-b9cc-51903035454e · inbound
Critical Appraisal of Fairness Metrics in Clinical Predictive AI cites this paper.
Critical Appraisal of Fairness Metrics in Clinical Predictive AI Fairness-enhancing mixed effects deep learning improves fairness on in- and out-of-distribution clustered (non-iid) data
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:35:04.055153Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc40fc4e-b01d-48c7-b1c0-161b48ffe6e1 · inbound
SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework cites this paper.
SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework Fairness-enhancing mixed effects deep learning improves fairness on in- and out-of-distribution clustered (non-iid) data
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T21:16:38.325119Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e578f961-d32a-4b50-a6b2-627c6e8c160c · inbound
SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework cites this paper.
SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework Fairness-enhancing mixed effects deep learning improves fairness on in- and out-of-distribution clustered (non-iid) data
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T22:18:27.663767Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1283f91c-5bd6-46e9-b9e7-8692232a19ed · inbound
SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework cites this paper.
SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework Fairness-enhancing mixed effects deep learning improves fairness on in- and out-of-distribution clustered (non-iid) data
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T06:03:27.925920Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.