Pith Number

pith:UE6LXVO7

pith:2025:UE6LXVO7OQYNZ5MM3RFCOPA3FP

not attested not anchored not stored refs pending

Process-Informed Forecasting of Complex Thermal Dynamics in Pharmaceutical Manufacturing

Aniruddha Bora, George Em Karniadakis, Michele Dassisti, Ramona Rubini, Siavash Khodakarami

Embedding deterministic production recipes as priors lets forecasting models for lyophilization temperatures outperform purely data-driven methods in accuracy, physical consistency, and noise resistance.

arxiv:2509.20349 v3 · 2025-09-24 · cs.LG

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\usepackage{pith}
\pithnumber{UE6LXVO7OQYNZ5MM3RFCOPA3FP}

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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

Our results show that PIF models outperform their data-driven counterparts in terms of accuracy, physical plausibility and noise resilience, offering a scalable framework for reliable and generalizable forecasting solutions in critical manufacturing.

C2weakest assumption

Deterministic production recipes provide accurate and unbiased macro-structural priors for the underlying thermal dynamics (abstract, description of embedding process-informed trajectory prior).

C3one line summary

PIF models incorporating production recipes as trajectory priors outperform purely data-driven models in accuracy, physical plausibility, and noise resilience for thermal forecasting in pharmaceutical manufacturing.

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:01:35.497282Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

a13cbbd5df7430dcf58cdc4a273c1b2bee464b10a2dd72d1427cc262fed7993d

Aliases

arxiv: 2509.20349 · arxiv_version: 2509.20349v3 · doi: 10.48550/arxiv.2509.20349 · pith_short_12: UE6LXVO7OQYN · pith_short_16: UE6LXVO7OQYNZ5MM · pith_short_8: UE6LXVO7

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/UE6LXVO7OQYNZ5MM3RFCOPA3FP \
  | 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: a13cbbd5df7430dcf58cdc4a273c1b2bee464b10a2dd72d1427cc262fed7993d

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "3f77098656367f81488e2aa355631bce6c2e1455d833d840780c075c717ffc5a",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2025-09-24T17:42:00Z",
    "title_canon_sha256": "0e74dd6472d665e621066a81c3097dadf58076b8be563984d164e91a4778c7b2"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2509.20349",
    "kind": "arxiv",
    "version": 3
  }
}