Pith Number

pith:BHOGF3DG

pith:2026:BHOGF3DGCUPLN6W7RBMXZZT5JG

not attested not anchored not stored refs pending

Stabilizing In-Context Multi-Source Domain Adaptation for Biomedical Images Through Controls

Ana Sanchez-Fernandez, G\"unter Klambauer, Thomas Pinetz, Werner Zellinger

Negative control samples present in every batch let meta-learning adapt models to new experimental conditions and close the domain gap in biomedical imaging.

arxiv:2604.20824 v2 · 2026-04-22 · cs.LG · q-bio.QM

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\usepackage{pith}
\pithnumber{BHOGF3DGCUPLN6W7RBMXZZT5JG}

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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

We are the first to show that meta-learning approaches close the domain gap by achieving 0.935 ± 0.018.

C2weakest assumption

Negative control samples are present in every experimental batch by design and serve as stable, unperturbed context for adaptation without introducing their own bias or domain shift.

C3one line summary

Meta-learning with in-context control samples closes the domain gap for mechanism-of-action classification, raising accuracy on new batches from 0.862 to 0.935 on the JUMP-CP dataset.

Receipt and verification

First computed	2026-06-23T03:13:57.403003Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

09dc62ec66151eb6fadf88597ce67d4987786b9ea5621a1259c27b1786fe4980

Aliases

arxiv: 2604.20824 · arxiv_version: 2604.20824v2 · doi: 10.48550/arxiv.2604.20824 · pith_short_12: BHOGF3DGCUPL · pith_short_16: BHOGF3DGCUPLN6W7 · pith_short_8: BHOGF3DG

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/BHOGF3DGCUPLN6W7RBMXZZT5JG \
  | 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: 09dc62ec66151eb6fadf88597ce67d4987786b9ea5621a1259c27b1786fe4980

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "0c662f0868bb436522218cbdc555502301333d9cf7bc180f5be8a8225b07efde",
    "cross_cats_sorted": [
      "q-bio.QM"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-04-22T17:49:00Z",
    "title_canon_sha256": "d8d7d67437b8958eae7c614d023e275f3c6851726c9edd4e520178e542e6934b"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.20824",
    "kind": "arxiv",
    "version": 2
  }
}