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 "@id": "https://wulfkaal.github.io/entities/evidence",
 "identifier": "kaal:entity:evidence",
 "name": "Evidence",
 "termCode": "evidence",
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 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
 },
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   "value": 2
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   "value": [
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  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/2998033-010",
   "identifier": "kaal:claim:2998033-010",
   "text": "Fears that technologically untrained judges will misunderstand blockchain are overstated, because blockchain is no different from other software that courts have already evaluated, and courts assisted by well trained attorneys should be able to appreciate its significance.",
   "abstract": "While some judges, untrained in technology and technology novices on the bench, could misunderstand and misinterpret the new technology, the technology is no different from other software that courts have evaluated.",
   "citation": "Wulf A. Kaal, Blockchain Innovation for Private Investment Funds (2017). SSRN: https://ssrn.com/abstract=2998033",
   "datePublished": "2017",
   "claim_type": "mechanism",
   "confidence": "argued",
   "is_failure_mode": false,
   "scope_conditions": [],
   "source_pdf_sha256": "aafb1be3c25cd33da477d759df9ca2f856f0a8fe133d6396da2e75d0af573dbd",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/7598518-044",
   "identifier": "kaal:claim:7598518-044",
   "text": "Because the simulated validators err independently given an accuracy that depends only on the tag, shared lineage, correlated errors, and error that depends on whether content is rare are excluded by construction, and the study supplies no evidence about correlated assessors or about reputation concentrating in a lineage.",
   "abstract": "Intelligence models increasingly learn from data that earlier Intelligence models produced, and when that loop repeats the rare cases disappear first. This paper preregisters a test of whether a reputation-weighted validator pool, filtering the training data of a recursive replacement loop, keeps those rare cases alive. The outcomes remain sealed until a replication of the original model-collapse result succeeds.",
   "citation": "Wulf A. Kaal, Can Reputation Prevent Model Collapse? A Preregistered Test of Reputation-Weighted Data Filtering (2026). SSRN: https://ssrn.com/abstract=7598518",
   "datePublished": "2026",
   "claim_type": "condition",
   "confidence": "stated",
   "is_failure_mode": true,
   "scope_conditions": [
    "The exclusion is a property of the simulation, not an observed null.",
    "Correlated assessors are among the conditions a reputation mechanism would face in deployment."
   ],
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  }
 ],
 "description": "2 claims in the published works of Wulf A. Kaal carry the concept tag 'evidence'. Derived node: a roster, not an adjudicated definition."
}