proof blockPage 490%
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First-See-Then-Design: A Multi-Stakeholder View for Optimal Performance-Fairness Trade-Offs explores A new framework for algorithmic decision-making that explicitly models multi-stakeholder utilities to achieve optimal performance-fairness trade-offs.. Commercial viability score: 4/10 in Fairness in AI.
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Page Freshness
Canonical route: /paper/first-see-then-design-a-multi-stakeholder-view-for-optimal-performance-fairness-trade-offs
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 first-see-then-design-a-multi-stakeholder-view-for-optimal-performance-fairness-trade-offs | Route /paper/first-see-then-design-a-multi-stakeholder-view-for-optimal-performance-fairness-trade-offs
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/first-see-then-design-a-multi-stakeholder-view-for-optimal-performance-fairness-trade-offsMCP example
{
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}Paper proof page receipt window
/buildability/first-see-then-design-a-multi-stakeholder-view-for-optimal-performance-fairness-trade-offs
Subject: First-See-Then-Design: A Multi-Stakeholder View for Optimal Performance-Fairness Trade-Offs
Verdict
Ignore
Verdict is Ignore because current viability and proof state do not clear the buildability gate.
Time to first demo
Insufficient data
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Structured compute envelope
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Dimensions overall score 4.0
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This equation defines the score or evaluation function that determines model quality.
Page and bbox are available; crop image is pending.
Owned Distribution
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Receipt path
/buildability/first-see-then-design-a-multi-stakeholder-view-for-optimal-performance-fairness-trade-offs
Paper ref
first-see-then-design-a-multi-stakeholder-view-for-optimal-performance-fairness-trade-offs
arXiv id
2604.14035
Generated at
2026-04-16T18:20:57.995Z
Evidence freshness
stale
Last verification
2026-04-16T18:20:57.995Z
Sources
3
References
0
Coverage
50%
Lineage hash
84464aedf36339bd5a89c31bd0f3f45fb34f17f4c9ef7831866854695431c3da
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
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Verification
not_verified
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Pending verification refs / 3 sources / Verification pending
repo_url
references
This equation captures one of the core mathematical components of the system. 𝐷∈{0, 1} and outcome 𝑌∈{0, 1}, potentially dependent on the non-sensitive features 𝑋. This formulation
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This equation defines the loss the model is optimizing during training. First-See-Then-Design: A Multi-Stakeholder View for Optimal
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