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pith:6RASYPHO

pith:2026:6RASYPHO7UT6FTWBAKNPXDV3TE
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An Empirical Analysis of Calibration and Selective Prediction in Multimodal Clinical Condition Classification

Farah E. Shamout, L. Juli\'an Lechuga L\'opez, Tim G. J. Rudner

Selective prediction degrades performance in multimodal clinical condition classification due to class-dependent miscalibration.

arxiv:2603.02719 v4 · 2026-03-03 · cs.LG

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\pithnumber{6RASYPHO7UT6FTWBAKNPXDV3TE}

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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

selective prediction can substantially degrade performance despite strong standard evaluation metrics. This failure is driven by severe class-dependent miscalibration, whereby models assign high uncertainty to correct predictions and low uncertainty to incorrect ones, particularly for underrepresented clinical conditions.

C2weakest assumption

The assumption that the tested unimodal and multimodal models and the specific ICU dataset splits are representative enough to generalize the miscalibration failure mode to broader clinical deployment scenarios.

C3one line summary

Selective prediction degrades performance in multimodal clinical condition classification due to class-dependent miscalibration that assigns high uncertainty to correct predictions and low uncertainty to incorrect ones.

Formal links

2 machine-checked theorem links

Receipt and verification
First computed 2026-05-25T02:01:16.410236Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

f4412c3ceefd27e2cec1029afb8ebb99229ab5b4e87a300eb7a30a76661d46b4

Aliases

arxiv: 2603.02719 · arxiv_version: 2603.02719v4 · doi: 10.48550/arxiv.2603.02719 · pith_short_12: 6RASYPHO7UT6 · pith_short_16: 6RASYPHO7UT6FTWB · pith_short_8: 6RASYPHO
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/6RASYPHO7UT6FTWBAKNPXDV3TE \
  | 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: f4412c3ceefd27e2cec1029afb8ebb99229ab5b4e87a300eb7a30a76661d46b4
Canonical record JSON
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-03-03T08:16:44Z",
    "title_canon_sha256": "5e02b3714c0b0fb9b21434dc387c6521ff0d270d6dba06fe3ddeb9f511df5d91"
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