{
 "@context": "https://schema.org",
 "@type": "DefinedTerm",
 "@id": "https://wulfkaal.github.io/entities/caps",
 "identifier": "kaal:entity:caps",
 "name": "Caps",
 "termCode": "caps",
 "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/caps.md",
 "sha256": "25e2e82cb9d951d4a8f4df9e209251addb31c8f00e7eee3c8889f973369b58d6",
 "additionalProperty": [
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   "@type": "PropertyValue",
   "name": "status",
   "value": "derived"
  },
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   "name": "claim_count",
   "value": 4
  },
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   "name": "work_count",
   "value": 2
  },
  {
   "@type": "PropertyValue",
   "name": "year_span",
   "value": [
    "2020",
    "2026"
   ]
  },
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   "@type": "PropertyValue",
   "name": "non_current_claims",
   "value": 0
  }
 ],
 "subjectOf": [
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/3606663-011",
   "identifier": "kaal:claim:3606663-011",
   "text": "Capped ICO raises, adopted by the crypto community to reduce investor uncertainty about platform valuation in uncapped raises, backfire because the cap creates strong incentives for investors to get in first, raising the likelihood of retail investor frenzy.",
   "abstract": "However, capped ICO raises create significant incentives for investors to attempt to get in first, raising the likelihood of retail investor frenzy.",
   "citation": "Kaal, Digital Asset Market Evolution (2020). SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3606663",
   "datePublished": "2020",
   "claim_type": "failure",
   "confidence": "argued",
   "is_failure_mode": true,
   "scope_conditions": [
    "capped ICO raises",
    "retail investor participation"
   ],
   "source_pdf_sha256": "d1d4a15a293b715bb6a5a32e689f59c3a1587915039ba9a1cf4eeb8ee2a1e57c",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/7598518-023",
   "identifier": "kaal:claim:7598518-023",
   "text": "The primary outcome caps each rare component's retained mass at its original level and averages over components, so that a component which dies counts as a loss and a component which grows cannot offset it.",
   "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": "design",
   "confidence": "stated",
   "is_failure_mode": false,
   "scope_conditions": [
    "The cap responds to total rare-region mass behaving close to a martingale under resampling, where individual components drift and die while the aggregate stays near its starting value.",
    "Uncapped rare mass is reported beside the capped outcome, supports no claim, and shows only what the cap changed."
   ],
   "source_pdf_sha256": "cd22d148b2b55c2e27f087dcaa61cdf44ad7022b400b355c31a9cd7e43a31749",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/7598518-041",
   "identifier": "kaal:claim:7598518-041",
   "text": "A positive reading would not say the weights mattered: the attribution sentence is issued only if the pool's contrast against full replacement and the reputation pool's contrast against the equal-weight pool are both superior in every family including the homogeneous one, the oracle premise and ladder rungs 3 and 4 pass in every family, and the key cap holds.",
   "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": false,
   "scope_conditions": [
    "The positive reading and the attribution sentence are distinct registered claims with distinct conditions.",
    "If the reputation contrast is null or negative in any family, the paper may say only that any difference is not attributable to reputation over equal weighting."
   ],
   "source_pdf_sha256": "cd22d148b2b55c2e27f087dcaa61cdf44ad7022b400b355c31a9cd7e43a31749",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/7598518-042",
   "identifier": "kaal:claim:7598518-042",
   "text": "The design names a failure pattern in advance: if the likelihood filter, the equal-weight pool, and the reputation pool each carry the negative label against full replacement in every family, the paper issues a registered sentence recording that each had lower capped retention at generation 50 than full replacement, as a registered negative result and not an implementation failure.",
   "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": "design",
   "confidence": "stated",
   "is_failure_mode": true,
   "scope_conditions": [
    "The sentence is available only on the stated pattern of labels in every family.",
    "Naming the pattern in advance is what distinguishes it from a post hoc explanation of a bad result."
   ],
   "source_pdf_sha256": "cd22d148b2b55c2e27f087dcaa61cdf44ad7022b400b355c31a9cd7e43a31749",
   "status": "current"
  }
 ],
 "description": "4 claims in the published works of Wulf A. Kaal carry the concept tag 'caps'. Derived node: a roster, not an adjudicated definition."
}