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  "text": "Mode B remains above 0.90 simulated accuracy up to a 0.49 Sybil share, but unspecified detector and update components prevent this result from establishing Sybil resistance.",
  "author": {
    "@type": "Person",
    "name": "Wulf A. Kaal",
    "identifier": "https://orcid.org/0009-0008-7840-1847"
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  "citation": "Wulf A. Kaal, Reinforcement Learning from Reputation Feedback (2026). SSRN: https://ssrn.com/abstract=7456999",
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    "name": "Reinforcement Learning from Reputation Feedback",
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  "abstract": "In this parameterized simulation, Mode B, the discrete two-round architecture, holds mean accuracy above 0.90 up to a Sybil fraction of 0.49 across 600 trials. Mode A, the continuous-coupling schedule, reaches 0.874 under the same conditions. Because the detector, dispersion statistic, threshold, false-positive and false-negative model, u p d a t e , t h e R o u n d 2 u p d a t e , a n d are unspeci\ufb01ed, this \ufb01gure is not evidence that the Sybil-resistance design objective has been achieved.",
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