Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Advancing Pavement Distress Detection in Developing Countries: A Novel Deep Learning Approach with Locally-Collected Datasets
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.05649.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:56:21.214273Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T00:56:22.201284Z
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 ca438c30-f0b1-4a4b-b7b6-6cf21d5edb17 · inbound
Demographics-Informed Neural Network for Multi-Modal Spatiotemporal forecasting of Urban Growth and Travel Patterns Using Satellite Imagery cites this paper.
Demographics-Informed Neural Network for Multi-Modal Spatiotemporal forecasting of Urban Growth and Travel Patterns Using Satellite Imagery Advancing Pavement Distress Detection in Developing Countries: A Novel Deep Learning Approach with Locally-Collected Datasets
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T00:56:22.205283Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 75a2c774-46a7-402d-a655-4753ca314c3d · inbound
PaveSync: A Unified and Comprehensive Dataset for Pavement Distress Analysis and Classification cites this paper.
PaveSync: A Unified and Comprehensive Dataset for Pavement Distress Analysis and Classification Advancing Pavement Distress Detection in Developing Countries: A Novel Deep Learning Approach with Locally-Collected Datasets
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T14:32:49.497968Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.