Research Program / Claims / distortion-7

Scientific instruments carry inherent systematic distortion effects that simplify and skew raw information from unknown data.

科学工具带有固有条扭曲效应，会将未知数据简化并歪曲原始信息。

Concept distortion · Domain Extended Perception and Consciousness Transduction · methodological suggestion · interface 3/3 · testability 3/3 · status supported

This program treats the Seth Material as a source of hypotheses, not as doctrine to be validated. Lead dossiers are AI-compiled from the corpus with a book-and-session citation after every statement; literature reviews are AI web-search summaries whose references were all DOI-verified against Crossref; the agenda draft is an AI synthesis. None of it is Seth's original text, and none of it represents scientific consensus. English fields are machine-translated; the Chinese text is authoritative.

Seth sources (book §session)
  • dreams-projections §2
Adjudicating experiment
Conduct a blinded comparison across 5 laboratories, inputting approximately 1000 known waveforms into three types of sensors with different principles, cross-manipulating bandwidth, dynamic range, noise, and preprocessing, comparing deviation, information loss, and interval coverage between raw and calibrated data, duration 6-9 months. For unknown samples, use cross-principle measurement for validation; without an independent reference, one cannot claim to have measured all raw information.
Suggested paper title
Instrument Response and Information Loss in a Preregistered Interlaboratory Measurement Study
What it would overturn
No need to overturn mainstream assumptions: modern metrology already clearly rejects the assumption that 'instrument readings naturally equal error-free true values.'
Candidate labs / funders
National Institute of Standards and Technology; Antonio Possolo，测量不确定度与计量统计研究者
Specificity of Seth's formulation
Lacks transfer functions, noise distributions, and correctable ranges, so it is less specific than metrological models; the strong version that 'instruments necessarily cannot know unknown things' is not supported.
Note
Supported only in the sense that finite bandwidth, noise, and models cause selective recording and error; uncertainty does not equal already-occurring systematic distortion, calibration can reduce bias, research direction see [NIST](https://www.nist.gov/people/antonio-possolo).
Evidence (1, DOI-verified via Crossref)

Cite: Future Mind Institute, Seth Material Research Agenda, claim distortion-7, https://www.seth.org.cn/en/research/claims/distortion-7