Pith Number

pith:RGEEDHKD

pith:2026:RGEEDHKDT34TO24TN3ST2K3PFZ

not attested not anchored not stored refs resolved

CitePrism: Human-in-the-Loop AI for Citation Auditing and Editorial Integrity

Binh Vu, Budanur Madappa Darshan Gowda, Gowrika Mahesh, Kavana Gopladevarahalli Papegowda, Mehrdad Jalali, Prajwal Basavaraj, Swati Chandna

CitePrism combines AI analysis with human review to help editors audit citation relevance and integrity.

arxiv:2605.16000 v1 · 2026-05-15 · cs.SI · cs.AI · cs.DL

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\usepackage{pith}
\pithnumber{RGEEDHKDT34TO24TN3ST2K3PFZ}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

These results suggest that CitePrism may support conservative editorial screening and citation-quality triage, but they do not establish general editorial performance.

C2weakest assumption

The agreement level and flagging performance observed in the preliminary validation on a single case-study manuscript from pavement engineering will hold for other manuscripts, domains, and annotators.

C3one line summary

CitePrism is a human-in-the-loop AI framework for auditing manuscript citations that demonstrated moderate agreement with human relevance judgments in a pilot validation on one paper.

References

32 extracted · 32 resolved · 1 Pith anchors

[1] M. Biagioli and A. Lippman,Gaming the Metrics: Misconduct and Manipulation in Academic Research. Cambridge, MA: MIT Press, 2020 2020

[2] Citation context analysis as a method for conducting rigorous and impactful literature reviews, 2021

[3] COPE guidelines on authorship and contributorship, 2023

[4] Self-citations: Necessary evil or sign of limited scholar- ship? 2020

[5] The global burden of journal peer review and the literature on peer review, 2016

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-20T00:01:48.393927Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

8988419d439ef9376b936ee53d2b6f2e52c07e2351f68d767f688c54c9dad4b8

Aliases

arxiv: 2605.16000 · arxiv_version: 2605.16000v1 · doi: 10.48550/arxiv.2605.16000 · pith_short_12: RGEEDHKDT34T · pith_short_16: RGEEDHKDT34TO24T · pith_short_8: RGEEDHKD

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/RGEEDHKDT34TO24TN3ST2K3PFZ \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 8988419d439ef9376b936ee53d2b6f2e52c07e2351f68d767f688c54c9dad4b8

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "de35921223b83dbc867e901666dca9ff401ae27aa9a263c465af3ba046da08c3",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.DL"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.SI",
    "submitted_at": "2026-05-15T14:31:45Z",
    "title_canon_sha256": "ab77b7fa25c8fd5a6a51eeed76fe8e616bf22ee3ddb75c6a6606d164c657a799"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.16000",
    "kind": "arxiv",
    "version": 1
  }
}