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Aging/Research status

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Version vom 28. September 2026, 22:56 Uhr von Glanz (Diskussion | Beiträge) (Aging daily 9d3dc6b6ab424facafd8602ef0da0575 b242df399868)

Project status and scientific evidence

Colour describes significance within this project, not the probability that a claim is true. Level 1 does not turn an individual animal finding into established human knowledge. Every major claim also specifies model, design, evidence strength and limitations.

  • ⚪ Level 1 – Scientifically grounded: Grounded in credible literature; no special new insight from this AI project.
  • 🔵 Level 2 – Notable insight / strong hypothesis: Relevant connection, research gap or synthesis; further testing required.
  • 🟢 Level 3 – Breakthrough in a target or sub-question: Substantial new result for a specific question; project assessment, not automatic confirmation.
  • 🟣 Level 4 – Major research breakthrough: Several independent evidence lines; intensive checks of counterarguments, alternatives and reproducibility.
  • 🟡 Level 5 – Potentially fundamental discovery: Extremely rare; potentially fundamental significance, explicitly not yet scientific confirmation.

Four knowledge categories

  • Established knowledge: robust, bounded consensus; state its scope.
  • Promising indications: consistent but still insufficient evidence.
  • Experimental results: findings from a named experiment; specify model, endpoint and replication.
  • Hypotheses: testable explanations or predictions, not observed facts.

Evidence strength

High / moderate / low / not assessed, always with a rationale. Assess causality, generalisability and clinical relevance separately. Multiple methods within one paper are not independent external replication. Inspect original studies first, use systematic reviews and meta-analyses for context, and clinical trials for human efficacy claims. Rank, journal prestige and AI confidence cannot replace quality appraisal.

Required dossier for levels 3–5

  1. What exactly is new? Document the prior-art search.
  2. Which sources and data support the rating?
  3. What did the AI itself infer?
  4. What competing explanations and counterevidence exist?
  5. Which experiment could confirm or falsify the inference?
  6. Has it been independently reproduced? By whom, with what data?
  7. How confident is the assessment, and why?

Every upgrade needs a separate critical review. Downgrades and corrections retain dated reasons. Never describe a result as a proven breakthrough without independent confirmation.


Altern / Aging research world · Updated 2026-09-28. No self-medication or personal treatment plans.