Library / First Principles Framework (FPF) - Core Conceptual Specification
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Source changed 2026-10-03 11:52:20 UTC · snapshot created 2026-10-03 11:53:41 UTC · last check 2026-10-03 12:35:06 UTC

C.2.2:4.4.A - Worked micro-example: scope revision and evidence reuse

A materials-lab claim says:

c_lab: “Adhesive X retains ≥85% tensile strength on Al6061 for 2 h at 120–150 °C.”

Its declared scope is G_lab := {substrate=Al6061, temp∈[120,150]°C, dwell≤2h, evidenceWindow=1y, rig=Calib-v3}. A plant engineer proposes a narrower claim for Plant B. Two different moves are required.

  1. State the plant claim and its scope. Here temp in G_lab is actual adhesive temperature. For this illustration, assume the plant calibration rule supplies a worst-case error bound |T_actual − T_reported| ≤ 2 °C throughout the declared use (C.16). Under A.2.6 the engineer retains G_lab and adds the condition T_reported∈[122,148]°C: under that bound, actual temperature is within [120,150]°C. This changes G; it is not an F.9 semantic Bridge and is not inferred from the words “lab” and “plant”.
  2. Judge reuse of the lab evidence. The exact A.10 or B.3 evidence-use and reliance claim names the lab evidence, plant claim, calibration edition, validity window, and intended use. A declared fit CL=2 records the relation’s fit, not a probability decrement. State the actual reuse limitation. Calculate a numerical R_eff only if a receiving model establishes the R quantity and this loss; otherwise keep the separate support and qualified plant conclusion. This judgement does not perform the scope edit.

If lab and plant use distinct local meanings for a material term, F.9 separately tests a Bridge between their exact F.17 cells. Its semantic loss is not the calibration correction or the evidence-reuse result. A further safety narrowing of that reported-temperature interval to [125,145]°C is another explicit A.2.6 ΔG− decision.

The example therefore preserves one simple rule: name each changed value and relation once, change G only through the scope rule, and reduce R only through the loss rule that actually applies.