Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM

Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/learning-who-disagrees-demographic-importance-weighting-for-modeling-annotator-distributions-with-diadem

stale

Proof freshness: stale
Proof status: unverified
Display score: 7/10
Last proof check: 2026-04-10
Score updated: 2026-04-10
Score fresh until: 2026-05-10
References: 0
Source count: 3
Coverage: 50%

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 learning-who-disagrees-demographic-importance-weighting-for-modeling-annotator-distributions-with-diadem | Route /signal-canvas/learning-who-disagrees-demographic-importance-weighting-for-modeling-annotator-distributions-with-diadem

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/learning-who-disagrees-demographic-importance-weighting-for-modeling-annotator-distributions-with-diadem

MCP example

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    "query_text": "Summarize Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM"
  }
}

source_context

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Evidence Receipt

Route status: building

Claims: 0

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM

PDF: https://arxiv.org/pdf/2604.08425v1

Source count: 3

Coverage: 50%

Last proof check: 2026-04-10T17:38:01.641Z

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Watch and verify: Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM

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Subject: Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM

Verdict

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Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.

Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM

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