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Paper Citation Record · LEDGER

No New-Net

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1809.10483.

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

pith.paper-citation-record.v1
1809.10483 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:14:54.295805Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T17:26:06.448798Z

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 46ad69ff-6591-4f83-8e5b-bc5dcf49d356 · inbound

Fully Automatic Binary Glioma Grading based on Pre-Therapy MRI using 3D Convolutional Neural Networks cites this paper.

Fully Automatic Binary Glioma Grading based on Pre-Therapy MRI using 3D Convolutional Neural Networks No New-Net

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-14T15:14:54.295805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T15:14:54.295805Z digest=sha256:134dda609fbc8e2b7c2c2b986258c3aac1fdc783995f35e53efe4fc58bdafbab

Observation 0dfdee16-c25b-448f-92bd-9312e652df3b · inbound

DALight-3D: A Lightweight 3D U-Net for Brain Tumor Segmentation from Multi-Modal MRI cites this paper.

DALight-3D: A Lightweight 3D U-Net for Brain Tumor Segmentation from Multi-Modal MRI No New-Net

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T23:21:47.466292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-08T17:36:13.747188Z digest=sha256:9fd9eff7edc62e560dba0bd141746c891da38c2060f24306e56d4feb7c6ca893