RICIS-III Precision Diagnostics under GoalP

Precision diagnostics is formalized as a path-indexed residual system under the AGI/researchobjective GoalP. Diagnostic quality is not a single accuracy number: axes include sensitivity,specificity, false-negative risk, false-positive risk, evidence provenance, and reproducibility.Each axis carries a weight; unsolved axes appear as nonzero residuals. Structural simplification drops solved constraints. Any ranking that replaces the path index P is rejected (L1).Product-type singularities reduce by 0F ⊗ ∞G ⇒ R(F,G) µ −→ F ·G. The note resolves mapnode med-diagnostics at workflow trust level only

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-01
DOI
https://doi.org/10.5281/zenodo.22230600
Primary Topic
AI-based Problem Solving and Planning
Type
article
Field-Weighted Citation Impact
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article

RICIS-III Precision Diagnostics under GoalP

Дмитрий Алейников
Zenodo (CERN European Organization for Nuclear Research)
AI-based Problem Solving and Planning
article

RICIS-III Precision Diagnostics under GoalP

Дмитрий Алейников
article en

Abstract

Precision diagnostics is formalized as a path-indexed residual system under the AGI/researchobjective GoalP. Diagnostic quality is not a single accuracy number: axes include sensitivity,specificity, false-negative risk, false-positive risk, evidence provenance, and reproducibility.Each axis carries a weight; unsolved axes appear as nonzero residuals. Structural simplification drops solved constraints. Any ranking that replaces the path index P is rejected (L1).Product-type singularities reduce by 0F ⊗ ∞G ⇒ R(F,G) µ −→ F ·G. The note resolves mapnode med-diagnostics at workflow trust level only

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 8%
AI-based Problem Solving and Planning
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