{
 "@context": "https://schema.org",
 "@type": "DefinedTerm",
 "@id": "https://wulfkaal.github.io/entities/pilots",
 "identifier": "kaal:entity:pilots",
 "name": "Pilots",
 "termCode": "pilots",
 "inDefinedTermSet": {
  "@id": "https://wulfkaal.github.io/entities/index.json"
 },
 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
 },
 "canonicalForm": "https://wulfkaal.github.io/entities/pilots.md",
 "sha256": "09e6c7ab91822c45b3c2009961895766cf25f94fd6fe922f099c64e09c19a2e0",
 "additionalProperty": [
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   "@type": "PropertyValue",
   "name": "status",
   "value": "derived"
  },
  {
   "@type": "PropertyValue",
   "name": "claim_count",
   "value": 2
  },
  {
   "@type": "PropertyValue",
   "name": "work_count",
   "value": 2
  },
  {
   "@type": "PropertyValue",
   "name": "year_span",
   "value": [
    "2025",
    "2026"
   ]
  },
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   "name": "non_current_claims",
   "value": 0
  }
 ],
 "subjectOf": [
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/5454054-038",
   "identifier": "kaal:claim:5454054-038",
   "text": "The retention uplifts claimed for LER remain unvalidated: empirical pilots are needed to confirm them and to refine the smart contract designs, particularly for AI-personalized airdrops.",
   "abstract": "Empirical pilots are needed to validate retention uplifts and refine smart contract designs.",
   "citation": "Wulf A. Kaal, Liquid Equity Rewards (2025). SSRN: https://ssrn.com/abstract=5454054",
   "datePublished": "2025",
   "claim_type": "failure",
   "confidence": "asserted",
   "is_failure_mode": true,
   "scope_conditions": [
    "current state of evidence as of 2025"
   ],
   "source_pdf_sha256": "9f53a865e6f0e5424640779df8f9b50923cd7d05649301dd4cc727144749b6e6",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/7598518-035",
   "identifier": "kaal:claim:7598518-035",
   "text": "The preregistered pilot meant to confirm that every arm completes was never run, the confirmatory seeds ran without it, and the paper states that their later completion does not cure the skipped gate.",
   "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": "empirical",
   "confidence": "stated",
   "is_failure_mode": true,
   "scope_conditions": [
    "This is one of two disclosed departures from the frozen procedure.",
    "Both departures qualify every reading the paper would issue."
   ],
   "source_pdf_sha256": "cd22d148b2b55c2e27f087dcaa61cdf44ad7022b400b355c31a9cd7e43a31749",
   "status": "current"
  }
 ],
 "description": "2 claims in the published works of Wulf A. Kaal carry the concept tag 'pilots'. Derived node: a roster, not an adjudicated definition."
}