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Paper Citation Record · LEDGER

Don't Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.13796.

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

pith.paper-citation-record.v1
2401.13796 v5

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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:58:19.916429Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T20:58:20.007298Z

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 3b57f540-1bee-43e7-97a3-51eb9bd52208 · inbound

On the (Mis)Use of Machine Learning with Panel Data cites this paper.

On the (Mis)Use of Machine Learning with Panel Data Don't Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-12T20:58:20.012003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T20:58:19.916429Z digest=sha256:c1d6ff32085eafabfdabeffbcaa97404a03c0f5c622dbd59f042506c100e3493

Observation 548a1997-1ecb-4541-b94a-69e4e2762782 · inbound

A geometric and deep learning reproducible pipeline for monitoring floating anthropogenic debris in urban rivers using in situ cameras cites this paper.

A geometric and deep learning reproducible pipeline for monitoring floating anthropogenic debris in urban rivers using in situ cameras Don't Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-04T07:54:02.448308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:54:02.448308Z digest=sha256:b0f4a15be19231b10eaa5e9a441f503f699d99d9efc7f830fba92f7232a0825e