ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims

ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims | Signal Canvas | ScienceToStartup

Page Freshness

Signal Canvas proof surface

Canonical route: /signal-canvas/climatecheck-2026-scientific-fact-checking-and-disinformation-narrative-classification-of-climate-related-claims

stale

Proof freshness: stale
Proof status: unverified
Display score: 4/10
Last proof check: 2026-03-30
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 0
Source count: 10
Coverage: 33%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Canonical ID climatecheck-2026-scientific-fact-checking-and-disinformation-narrative-classification-of-climate-related-claims | Route /signal-canvas/climatecheck-2026-scientific-fact-checking-and-disinformation-narrative-classification-of-climate-related-claims

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/climatecheck-2026-scientific-fact-checking-and-disinformation-narrative-classification-of-climate-related-claims

MCP example

{
  "tool": "search_signal_canvas",
  "arguments": {
    "mode": "paper",
    "paper_ref": "climatecheck-2026-scientific-fact-checking-and-disinformation-narrative-classification-of-climate-related-claims",
    "query_text": "Summarize ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims"
  }
}

source_context

{
  "surface": "signal_canvas",
  "mode": "paper",
  "query": "ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims",
  "normalized_query": "2603.26449",
  "route": "/signal-canvas/climatecheck-2026-scientific-fact-checking-and-disinformation-narrative-classification-of-climate-related-claims",
  "paper_ref": "climatecheck-2026-scientific-fact-checking-and-disinformation-narrative-classification-of-climate-related-claims",
  "topic_slug": null,
  "benchmark_ref": null,
  "dataset_ref": null
}

Evidence Receipt

Route status: building

Claims: 8

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims

PDF: https://arxiv.org/pdf/2603.26449v1

Source count: 10

Coverage: 33%

Last proof check: 2026-03-30T21:58:24.828Z

Signal Canvas receipt window

Not build-ready: ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims

/buildability/climatecheck-2026-scientific-fact-checking-and-disinformation-narrative-classification-of-climate-related-claims

Ignoreblocked

Subject: ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims

Verdict

Ignore

Preparing verified analysis

GitHub Code Pulse

No public code linked for this paper yet.

Claim map

Strong 8Mixed 0Weak 0

Evidencepartial
we address these challenges and substantially expand the scope of our dataset. We release approx. three times more training data
Implicationpartial
The abstract explicitly states the expansion of training data.
Verificationpartial
partial
Evidencepartial
and introduce a new task,Disinformation Narrative Classification, which moves beyond claim-level verif
Implicationpartial
The abstract clearly states the introduction of a new task.
Verificationpartial
partial
Evidencepartial
The overall inter-annotator agreement (IAA) of the training split including the extension is Cohen’sκ = 0.73, indicating substan-tial agreement
Implicationpartial
This is a specific metric reported directly in the text.
Verificationpartial
partial
Evidencepartial
The selected checkpoint at step 26,000 (epoch 1.7) achieves a macro-F1 of 0.886 and an accuracy of 0.921 on the combined validation set
Implicationpartial
Specific performance metrics are provided for a selected checkpoint.
Verificationpartial
partial
Evidencepartial
DFKI-IML (Liang et al., 2026) 0.193 0.352 0.401 0.377 0.670 0.641 0.620 0.972
Implicationpartial
This is a specific result reported in Table 2, with the best result bolded.
Verificationpartial
partial
Evidencepartial
the competition attracted 20 registered participants and 8 leaderboard submissions
Implicationpartial
This information is directly stated in the abstract.
Verificationpartial
partial
Evidencepartial
with systems combining dense retrieval pipelines, cross-encoder ensembles, and large language models with structured hierarchical reasoning.
Implicationpartial
The abstract describes the common system architectures used by participants.
Verificationpartial
partial
Evidencepartial
we adapt an automated framework to assess retrieval quality under incomplete annotations, exposing systematic biases in how conventional metrics rank systems.
Implicationpartial
The abstract highlights a limitation and a finding related to evaluation metrics.
Verificationpartial
partial

Author intelligence and commercialization panels stay hidden until the proof receipt is verified, cites at least 3 references, includes at least 2 sources, and clears 50% coverage. The paper narrative and citation surfaces remain public while verification is pending.

ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims

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