The Initial Hypothesis

The initial product note imagined a simple public interaction on X: reply to a post with ~cortisolchecker, let a bot inspect the parent post, and receive a score, detected signals, a protocol trace, and one regulation suggestion. It was meant to make The Internet of Value tangible through a small real-world use case rather than through an abstract introduction.

The first conceptual equation was:

Final Score =

  Lexical Trigger Score

  + Context Threat Score

  + Social-Evaluative Threat Score

  + Outrage Mechanics Score

  - Calming Regulation Score

Its suggested bands were lexical 0–25, context threat 0–30, social-evaluative threat 0–25, outrage mechanics 0–20, and regulation 0 to -15, with the final result clamped to 0–100.

This was a design hypothesis, not the present algorithm. It established five useful ideas: keywords alone were insufficient; context mattered; public judgment deserved its own component; outrage mechanics should not be confused with serious content; and regulation cues should be able to reduce a result. But it did not yet specify deduplication, category boosts, semantic evidence, confidence, sensitive-content handling, or a reproducible contract.

The current 0.4.1 analysis engine preserves the decomposition but changes important details. Lexical evidence is deduplicated by category and capped at 28. Context threat is capped at 25. A semantic floor prevents high-harm language from being presented below the emotional-load band when the preliminary score is positive. Safety detection is a separate path. Confidence measures the amount of textual evidence, not confidence about a person's physiology.

External research supports investigating relationships between language and stress, but it does not validate this rubric. Laboratory work has found associations between physiological stress reactivity and changes in linguistic complexity (Saslow et al., 2014); social-media research has also shown that text can contain detectable markers associated with self-reported chronic stress (Yang et al., 2023). The current rubric is an open research prototype developed through iterative authoring and calibration. Its categories, phrases, and weights are published for inspection and criticism in How the Score Actually Works.

Keeping the early formula visible matters because it shows how the inquiry developed. Calling it “the algorithm,” however, would be inaccurate. This paper uses it only as historical evidence and uses executable 0.4.1 code and pinned fixtures for current claims.