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Paper Citation Record · LEDGER

What the F-measure doesn't measure: Features, Flaws, Fallacies and Fixes

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1503.06410.

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

pith.paper-citation-record.v1
1503.06410 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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:13:24.199605Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T11:24:58.177831Z

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 ef6832b8-7334-4654-bb75-50ba5040a9bd · inbound

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning cites this paper.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning What the F-measure doesn't measure: Features, Flaws, Fallacies and Fixes

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T05:13:24.199605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:13:24.199605Z digest=sha256:166b1bfe2f219befdb1a6436901b80d51ad8e7cd719915409283017ab1ccd12f

Observation 1c4d92a0-b198-4063-9db0-85667adf42fe · inbound

Multi-Scale Deep Learning for Colon Histopathology: A Hybrid Graph-Transformer Approach cites this paper.

Multi-Scale Deep Learning for Colon Histopathology: A Hybrid Graph-Transformer Approach What the F-measure doesn't measure: Features, Flaws, Fallacies and Fixes

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-05T11:24:58.232184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-05T11:24:57.302631Z digest=sha256:f9375d6a334263fc4409aa905061a69615259c5dd8a81edce49e004150485c85