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Paper Citation Record · LEDGER

Refnd: Preventing Data Leakage in Relational Datasets

As of 19 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2607.19376.

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

pith.paper-citation-record.v1
2607.19376 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T09:17:18.180681Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:26:52.616368Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T04:26:52.804893Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact10
  • verified fuzzy0
  • unresolved13
  • parse uncertain0
  • malformed identifier7
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 382a34ad-2906-4be7-bd24-d4217c96f9e2 · outbound

This paper cites Do ImageNet Classifiers Generalize to ImageNet?,.

Refnd: Preventing Data Leakage in Relational Datasets Do ImageNet Classifiers Generalize to ImageNet?,

Reference 1

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no resolver link, observed 2026-08-02T09:17:15.331150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9aae220a-5115-4d7a-bc98-04324f7c009c · outbound

This paper cites Hastie, R.

Refnd: Preventing Data Leakage in Relational Datasets Hastie, R

Reference 2

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no resolver link, observed 2026-08-02T09:17:15.413600Z

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Unavailable: canonical work link unavailable.

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Observation f14448c1-b3d4-4270-9e32-7c769915cc2f · outbound

This paper cites Cracking the black box of deep sequence-based protein–protein interaction prediction,.

Refnd: Preventing Data Leakage in Relational Datasets Cracking the black box of deep sequence-based protein–protein interaction prediction,

Reference 3

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no resolver link, observed 2026-08-02T09:17:15.571466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a115d641-482d-4d1e-8d12-897b80991ad1 · outbound

This paper cites Leakage in data mining: Formulation, detection, and avoidance,.

Refnd: Preventing Data Leakage in Relational Datasets Leakage in data mining: Formulation, detection, and avoidance,

Reference 4

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no resolver link, observed 2026-08-02T09:17:15.682142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3f395f60-962e-4574-8cf8-19b435cc2957 · outbound

This paper cites Leakage and the reproducibility crisis in machine- learning-based science,.

Refnd: Preventing Data Leakage in Relational Datasets Leakage and the reproducibility crisis in machine- learning-based science,

Reference 5

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malformed identifier
no resolver link, observed 2026-08-02T09:17:15.780401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4e256359-ecec-4d7a-9717-a3b71703a2fe · outbound

This paper cites REFORMS: Consensus-based Recommendations for Machine-learning- based Science,.

Refnd: Preventing Data Leakage in Relational Datasets REFORMS: Consensus-based Recommendations for Machine-learning- based Science,

Reference 6

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malformed identifier
no resolver link, observed 2026-08-02T09:17:15.885321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9bb06874-67c8-4bae-98e3-1692990e5ab6 · outbound

This paper cites Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences,.

Refnd: Preventing Data Leakage in Relational Datasets Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences,

Reference 8

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verified exact
doi, observed 2026-08-02T09:18:26.428565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3a1503fb-0e24-4d6a-8ed6-db5fe936d031 · outbound

This paper cites Effect of dataset partitioning strategies for evaluating out-of-distribution generalisation for predictive models in biochem - istry.

Refnd: Preventing Data Leakage in Relational Datasets Effect of dataset partitioning strategies for evaluating out-of-distribution generalisation for predictive models in biochem - istry

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 67881109-731f-4998-8b68-027345b54f01 · outbound

This paper cites Mechanisms of protein evolution,.

Refnd: Preventing Data Leakage in Relational Datasets Mechanisms of protein evolution,

Reference 10

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verified exact
doi, observed 2026-08-02T09:18:26.127098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ade35ff1-56f6-496f-a403-7f025666978a · outbound

This paper cites An efficient algorithm for large-scale detection of protein families,.

Refnd: Preventing Data Leakage in Relational Datasets An efficient algorithm for large-scale detection of protein families,

Reference 11

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verified exact
doi, observed 2026-08-02T09:18:25.907701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 848a08c6-b125-4830-86bc-8c25b799dac1 · outbound

This paper cites The Properties of Known Drugs. 1. Molecular Frameworks,.

Refnd: Preventing Data Leakage in Relational Datasets The Properties of Known Drugs. 1. Molecular Frameworks,

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9cdad9d1-b389-4524-86a7-8ab6e71b1d10 · outbound

This paper cites Matched Molecular Pair Analysis in Drug Discovery: Methods and Recent Applications,.

Refnd: Preventing Data Leakage in Relational Datasets Matched Molecular Pair Analysis in Drug Discovery: Methods and Recent Applications,

Reference 13

Resolution
verified exact
doi, observed 2026-08-02T09:18:25.631319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8b56a6d2-2fb8-49e1-8022-79ef45cf14fe · outbound

This paper cites MoleculeNet: a benchmark for molecular machine learning,.

Refnd: Preventing Data Leakage in Relational Datasets MoleculeNet: a benchmark for molecular machine learning,

Reference 14

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no resolver link, observed 2026-08-02T09:17:16.638429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e756cfd6-371d-4711-ba53-5ae834615e77 · outbound

This paper cites QMAP: A Benchmark for Standardized Evaluation of Antimicrobial Peptide MIC and Hemolytic Activity Regression,.

Refnd: Preventing Data Leakage in Relational Datasets QMAP: A Benchmark for Standardized Evaluation of Antimicrobial Peptide MIC and Hemolytic Activity Regression,

Reference 15

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verified exact
doi, observed 2026-08-02T09:18:25.446100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d261f310-ec6e-4bc9-8c4a-4618d85365d4 · outbound

This paper cites DBAASP v3: database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics,.

Refnd: Preventing Data Leakage in Relational Datasets DBAASP v3: database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics,

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 42cbd8b1-7e00-4834-8e04-aeb69d4a9347 · outbound

This paper cites Data splitting to avoid information leakage with DataSAIL,.

Refnd: Preventing Data Leakage in Relational Datasets Data splitting to avoid information leakage with DataSAIL,

Reference 17

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malformed identifier
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b2f9f296-1e28-4f17-8bcd-87f0d3dd7456 · outbound

This paper cites Lo-Hi: Practical ML Drug Discovery Benchmark,.

Refnd: Preventing Data Leakage in Relational Datasets Lo-Hi: Practical ML Drug Discovery Benchmark,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-02T09:17:17.087083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b6c7f106-0758-40a2-8f51-241460979847 · outbound

This paper cites GraphPart: homology partitioning for biological sequence analysis,.

Refnd: Preventing Data Leakage in Relational Datasets GraphPart: homology partitioning for biological sequence analysis,

Reference 19

Resolution
verified exact
doi, observed 2026-08-02T09:18:25.333434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 92b45de0-e250-4d2c-bafb-ca4d819ace6d · outbound

This paper cites AutoPeptideML: a study on how to build more trustworthy peptide bioactivity predictors,.

Refnd: Preventing Data Leakage in Relational Datasets AutoPeptideML: a study on how to build more trustworthy peptide bioactivity predictors,

Reference 20

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 41bd7c11-0f0e-432a-99b0-8b6bc8a014b6 · outbound

This paper cites SpanSeq: similarity-based sequence data splitting method for improved development and assessment of deep learning projects,.

Refnd: Preventing Data Leakage in Relational Datasets SpanSeq: similarity-based sequence data splitting method for improved development and assessment of deep learning projects,

Reference 21

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation c795d991-2a5f-411a-a557-fb8d559c044f · outbound

This paper cites A density-based algorithm for discovering clusters in large spatial databases with noise,.

Refnd: Preventing Data Leakage in Relational Datasets A density-based algorithm for discovering clusters in large spatial databases with noise,

Reference 22

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6e134815-d4b1-4cc6-b731-cde92117a60e · outbound

This paper cites From Louvain to Leiden: guaranteeing well- connected communities,.

Refnd: Preventing Data Leakage in Relational Datasets From Louvain to Leiden: guaranteeing well- connected communities,

Reference 23

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Unavailable: canonical work link unavailable.

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Observation 4b48027c-d84b-4ff9-ad3e-6abcb7ee875c · outbound

This paper cites Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs,.

Refnd: Preventing Data Leakage in Relational Datasets Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs,

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c46e4b3c-fe87-4499-9251-daf9c2228258 · outbound

This paper cites Community Structure in Graphs,.

Refnd: Preventing Data Leakage in Relational Datasets Community Structure in Graphs,

Reference 25

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 6c408d3e-9aff-4553-a3c4-08197270723f · outbound

This paper cites Parasail: SIMD C library for global, semi-global, and local pairwise sequence align- ments,.

Refnd: Preventing Data Leakage in Relational Datasets Parasail: SIMD C library for global, semi-global, and local pairwise sequence align- ments,

Reference 26

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 71f3e003-dd07-44b6-a80f-c012b946ee69 · outbound

This paper cites US-align: universal structure alignments of proteins, nucleic acids, and macromolecular complexes,.

Refnd: Preventing Data Leakage in Relational Datasets US-align: universal structure alignments of proteins, nucleic acids, and macromolecular complexes,

Reference 27

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 92cc6e62-2b67-4a2e-aea0-87b9406d2848 · outbound

This paper cites Evolutionary-scale prediction of atomic-level protein structure with a language model,.

Refnd: Preventing Data Leakage in Relational Datasets Evolutionary-scale prediction of atomic-level protein structure with a language model,

Reference 28

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c254915a-5e31-49a4-a40d-1f39a85e5702 · outbound

This paper cites Identification of common molecular subsequences,.

Refnd: Preventing Data Leakage in Relational Datasets Identification of common molecular subsequences,

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-02T09:17:18.127880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3b9f6e7d-d2d3-4069-825d-c52304f22e6a · outbound

This paper cites A general method applicable to the search for similarities in the amino acid sequence of two proteins,.

Refnd: Preventing Data Leakage in Relational Datasets A general method applicable to the search for similarities in the amino acid sequence of two proteins,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-02T09:17:18.180681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6e10ec4f-46ed-49ef-979c-3ca2d56824cd · outbound

This paper cites Available: https://openreview.net/forum?id=H2Yb28qGLV.

Refnd: Preventing Data Leakage in Relational Datasets Available: https://openreview.net/forum?id=H2Yb28qGLV

Reference 2026

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

Observation a66b43db-033f-44c8-8391-c202067a4300 · inbound

A Symmetric Layer-Union Audit of Component Collapse in Hierarchical Procedural Corpora cites this paper.

A Symmetric Layer-Union Audit of Component Collapse in Hierarchical Procedural Corpora Refnd: Preventing Data Leakage in Relational Datasets

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-14T04:26:52.827847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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