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Paper Citation Record · LEDGER

Magika: AI-Powered Content-Type Detection

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.13768.

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

pith.paper-citation-record.v1
2409.13768 v1

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:42:16.037328Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T04:26:35.423577Z

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 7705bb0e-815f-49b1-807c-562b4b755778 · inbound

Agentic AI framework for End-to-End Medical Data Inference cites this paper.

Agentic AI framework for End-to-End Medical Data Inference Magika: AI-Powered Content-Type Detection

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T14:42:16.037328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:42:16.037328Z digest=sha256:2d6925d45b5275b358feb96ea2a9fa37d192a9b9818ef7640eefb0a871686bb6

Observation 94005951-33ee-4b3b-9737-cd39d0a63075 · inbound

MimeLens: Position-Agnostic Content-Type Detection for Binary Fragments cites this paper.

MimeLens: Position-Agnostic Content-Type Detection for Binary Fragments Magika: AI-Powered Content-Type Detection

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-02T04:26:35.425149Z

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.

source=pdf_text observed=2026-06-28T09:13:26.501298Z digest=sha256:5388c1f746511b382a534fbbdba8d2d61a8fa56c0b471d6e2b3ccbbbb487788d