How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Batch and measurement-process variation — Examples
1 · Prerequisites
- Batch and measurement-process variation
- Binary Operations, Monoids, Groups and Subgroups
- Calibration and measurement uncertainty
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Estimators and Randomized Procedures
- Finite Counting, Factorials and Binomial Coefficients
- Fixed-design regression, estimability, and Gauss–Markov
- Foundations of the Real Numbers for Analysis
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Independence Borel Cantelli and Zero One Laws
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Matrix Differentiation and First-order Spectral Perturbation
- Matrix Norms, Condition Numbers and Numerical Stability
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Mixed effects and longitudinal models
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Polynomial Rings, the Division Algorithm and Roots
- Probability Spaces Random Variables and Expectation
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Roots, Rational Powers, and Classical Inequalities
- Scientific model contracts and applicability
- Sequences and Limits
- Sigma Algebras and Borel Sets
- Simple Field Extensions and the Construction of the Complex Numbers
- Statistical Experiments, Models and Identifiability
- Suprema and Infima
- The Lebesgue Integral and the Convergence Theorems
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
Three stable reference standards are measured on two days under stipulated linear response curves. The worked calculations recover the day-specific slopes, fit the equally weighted pooled line, and compare its check-standard residuals and inverse readings with the separate curves. The example is deterministic and illustrates how a shared curve can conceal day-specific behavior; it makes no empirical, inferential, or general stability claim.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
Day-specific calibration slope drift and check standards
Example
Suppose the three stable reference standards have assigned quantities . Remeasure these same standards on two days, obtaining the stipulated exact response table
| Reference quantity | Day 1 response | Day 2 response |
|---|---|---|
Take as the declared calibration range. The standards are check standards here: fixed reference artifacts measured again over time to reveal changes in the measurement process. The numbers are a deterministic illustration, not observed data. Fit one equally weighted straight line with an intercept to all six response pairs and compare it with the separate day-specific calibration curves.
Facts & Assumptions
Given: The assigned reference values and stipulated responses in the Example, with the pooled line defined to minimize the sum of squared vertical residuals over all six pairs.
Measurands, calibration, and measurement uncertainty: a calibration curve is a specified relation between a reference quantity and instrument response used to convert a later response into a measurand estimate.
Batch and measurement-process variation: day is a batch/process condition, and calibration curves are pooled only under an explicit shared curve or equivalence model.
The three reference standards remain stable with assigned values on both days, and the response table is stipulated exactly as shown.
The pooled line is with , fitted by minimizing with equal weight for each of the six readings.
Verification
The day-specific lines are and : each intercept is the response at , and the slopes are and . In particular the known standard at has responses and .
The six reference values have mean and the six responses have mean . Their centered sums are and : the two readings contribute , the readings contribute , and the two readings contribute .
Write each residual as . The first two terms sum to zero over the six pairs, so expanding the sum of squared residuals gives . For fixed this is minimized at ; the remaining slope-dependent terms are , whose completed square is plus a constant. Since , the unique minimizing slope is and , giving .
At the check standard, the pooled line predicts , so its day-specific residuals are and . Inverting the pooled line maps the two observed responses to and , whereas the separate day lines each map their own response back to . The three-standard table exposes the differing slopes in this stipulated example; it supplies no empirical evidence, statistical test, or general justification for pooling calibration curves.
Remarks
There is one stipulated reading per standard per day, so the table does not estimate repeatability, a variance component, a control limit, or uncertainty. It only demonstrates the finite arithmetic of comparing three standard responses under two specified lines.