consumer concept

Definition	The function that acts on a vector, the first element of an observer. A softmax, a classifier, an index, a person reading a report. Chapter 1.
Example	A logistic classifier reading a 30-column table is a consumer; so is a cosine ranker, and so is a person reading a summary.
Book	Data Mining as Observation, draft 0.2, commit `f3914f0`; entry id `consumer`, kind concept.
Status	measures [predicted] ×2. Corrections: none recorded.
Defining equation	Book equation 1.1.
Assumptions and scope	A consumer is any computation that takes a vector in and gives an output out, a softmax, a classifier, an index, a person reading a report. The book’s quantities are functions of the consumer, and two consumers with the same read operator are not thereby the same consumer. A selection consumer, a tree or a threshold, has zero sensitivity almost everywhere and is read by counting where it selects rather than by finite differences.
Prior art	none recorded
Evidence	`geometric-observation/claims/LEDGER.md:62`, `geometric-observation/claims/LEDGER.md:162`, `readscope/readscope/regimes.py:1-60`, `geometric-observation/chapters/ch04_the_observer_triple.md:60-135`, `lean/DataMiningAsObservation/ReadOperator.lean`
Reviewed	not yet reviewed; generated 2026-09-10 from records at the commits on the provenance page.

The computation that reads the vector, the first element of the observer.

Equation

Book equation 1.1.

\[O=(C,\ G,\ B).\]

Conditions

A consumer is any computation that takes a vector in and gives an output out, a softmax, a classifier, an index, a person reading a report. The book’s quantities are functions of the consumer, and two consumers with the same read operator are not thereby the same consumer.
A selection consumer, a tree or a threshold, has zero sensitivity almost everywhere and is read by counting where it selects rather than by finite differences.

Conditions are curated in entries.toml rather than read from a record.

Ledger

measures. GO-1 [predicted]. The consumer’s invariant/nuisance split is identifiable ex ante from the consumer functional. geometric-observation/claims/LEDGER.md:62.
measures. GO-EC-3 [predicted]. A read operator recovered from a black-box consumer by query-only finite-difference probing, composed with the Kalman covariance as tr(P̂_C Σ), prospectively selects sensors that improve the held-out consumer at matched budgets with probe … geometric-observation/claims/LEDGER.md:162.

First stated

Volume 14, chapter 4, geometric-observation/chapters/ch04_the_observer_triple.md:9-60 and its consumer table at lines 60-135, DOI 10.5281/zenodo.21776291.

Measurements

Where the book states it	Numbers, as the book’s sources table records them	Source
chapter 2 section 2.3	refusal regimes, selection consumers read order, recurrences compound	`readscope/readscope/regimes.py:1-60`
chapter 6 section 6.1	the classifier row of the consumer table, the output metric makes a different observer	`geometric-observation/chapters/ch04_the_observer_triple.md:60-135`
chapter 6 section 6.1	selection consumers have zero sensitivity almost everywhere	`readscope/readscope/regimes.py:1-60`

Failures and corrections

none

Invariance envelope

none declared

Machine checked

lean/DataMiningAsObservation/ReadOperator.lean, theorems rank_one_reads_one_direction, readOp_mulVec, quad_readOp, quad_readOp_nonneg, readOp_mulVec_eq_zero_iff, readOp_diag, readOp_offdiag, readOp_symm, readOp_neg, affine_const_along_nuisance, readOp_affine, readOp_sqLength_basis, at observation-data-mining f3914f0; what the check covers is stated in the book’s appendix C.

Used in

Data Mining as Observation primer L, chapters 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14.

observer; read operator; sensitivity; budget.

Status

Generated 2026-09-10 by encyclopedia/generate.py; book at observation-data-mining f3914f0; the commit of every record is listed in the encyclopedia’s provenance.

← confusion matrixcontraction →