Pith Number

pith:P2AW4J6U

pith:2026:P2AW4J6UZLPTJPCX4GYYYWJZTX

not attested not anchored not stored refs resolved

PROMETHEUS: Automating Deep Causal Research Integrating Text, Data and Models

Sridhar Mahadevan

PROMETHEUS organizes causal claims extracted from text and data into sheaf-like local models over a research cover, with gluing diagnostics to expose agreements, contradictions, and gaps.

arxiv:2605.12835 v1 · 2026-05-13 · cs.AI

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\usepackage{pith}
\pithnumber{P2AW4J6UZLPTJPCX4GYYYWJZTX}

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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

The resulting Topos World Model is not a single universal graph. It is a research instrument for navigating what a corpus says, where it says it, how strongly it is supported, and where local claims fail to assemble into a coherent global view.

C2weakest assumption

That local causal claims extracted from text and data can be reliably organized into sheaf-like families whose restriction maps and gluing diagnostics accurately reflect the underlying research substrate without introducing significant artifacts or losing critical context.

C3one line summary

PROMETHEUS builds causal atlases from text and data using local predictive-state models and sheaf gluing to create navigable Topos World Models that expose evidence strength and coherence gaps.

References

25 extracted · 25 resolved · 1 Pith anchors

[1] The sheaf-theoretic structure of non-locality and contextuality 2011

[2] Automatic detection of causal relations for question answering 2003

[3] Causal knowledge extraction through large-scale text mining 2020

[4] A survey of event causality identification: Taxonomy, resources, and techniques 2023 · doi:10.1145/3582128

[5] SemEval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals 2010

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T03:09:12.043358Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

7e816e27d4cadf34bc57e1b18c59399deb7abd71cb5ac71121b59e55f536b29b

Aliases

arxiv: 2605.12835 · arxiv_version: 2605.12835v1 · doi: 10.48550/arxiv.2605.12835 · pith_short_12: P2AW4J6UZLPT · pith_short_16: P2AW4J6UZLPTJPCX · pith_short_8: P2AW4J6U

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/P2AW4J6UZLPTJPCX4GYYYWJZTX \
  | 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: 7e816e27d4cadf34bc57e1b18c59399deb7abd71cb5ac71121b59e55f536b29b

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "7c2009c0606f0ab8fa29acac7f63b7f1a9b478568097d19d19353621d2a5468a",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-05-13T00:08:07Z",
    "title_canon_sha256": "52048668887490189a03471219e95cf09e2c5eda2140d5380aa599dcf8b55671"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12835",
    "kind": "arxiv",
    "version": 1
  }
}