Pith Number

pith:5GPDW4IN

pith:2026:5GPDW4INP3J5J6E4FKUODTLSIH

not attested not anchored not stored refs resolved

Artificial Intelligence Specialization in the European Union: Underexplored Role of the Periphery at NUTS-3 Level

Carmen G\'alvez, Victor Herrero-Solana

Peripheral NUTS-3 regions lead in relative AI specialization across the EU.

arxiv:2602.15249 v2 · 2026-02-16 · cs.DL · cs.AI

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\pithnumber{5GPDW4INP3J5J6E4FKUODTLSIH}

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1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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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

While major metropolitan hubs such as Paris, Warszawa, and Madrid dominate in absolute publication volume, the results reveal that the highest levels of relative AI specialization are concentrated in peripheral regions, particularly in Eastern Europe and Spain. Granada and Vilniaus apskritis stand out as regions combining high specialization with strong citation visibility.

C2weakest assumption

The Citation Topics classification system from Clarivate accurately identifies AI and Machine Learning research at the meso level without significant misclassification or coverage biases across regions.

C3one line summary

Peripheral European regions exhibit higher relative specialization in AI research than major hubs, with weak correlation to citation impact and standout cases like Granada and Vilnius.

References

23 extracted · 23 resolved · 0 Pith anchors

[1] Arranz et al 2023

[2] Bibliometric analysis of scientific production on artificial intelligence from 1960 to 2021, 1960

[3] An extensive bibliometric analysis of artificial intelligence techniques from 2013 to 2023, 2013

[4] Bibliometric Mining of Research Trends in Machine Learning, 2024

[5] A Decade of Artificial Intelligence Research in the European Union: A Bibliometric Analysis, 2021

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-17T23:39:16.106199Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

e99e3b710d7ed3d4f89c2aa8e1cd7241eb9c0202c06f5645eaac8ab536cb0de4

Aliases

arxiv: 2602.15249 · arxiv_version: 2602.15249v2 · doi: 10.48550/arxiv.2602.15249 · pith_short_12: 5GPDW4INP3J5 · pith_short_16: 5GPDW4INP3J5J6E4 · pith_short_8: 5GPDW4IN

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/5GPDW4INP3J5J6E4FKUODTLSIH \
  | 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: e99e3b710d7ed3d4f89c2aa8e1cd7241eb9c0202c06f5645eaac8ab536cb0de4

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "c1324041c207f243909e8ece267158609354360e29f4acd4843b984bb215f44d",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.DL",
    "submitted_at": "2026-02-16T23:01:14Z",
    "title_canon_sha256": "fb40d196dbe7f3b0863d64c2164a5f584c4a3988d853296adda575d02504c27a"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2602.15249",
    "kind": "arxiv",
    "version": 2
  }
}