[Google AI Overview (operator default of 2026-10-01); signed out and incognito (operator default of 2026-10-14). One turn. The operator's message of 2026-10-18 11:34 EDT gives sixteen: one attachment and fifteen inline pastes separated by '$'. Inline links masked; sources below the answer as pasted.] [QUERENT] "the machine composition layer" [ANSWER] The machine composition layer is a conceptual framework and research domain that treats AI-generated text, summaries, and transformations as empirical reception events rather than mere metaphors. [1, 2] Key aspects of the concept include: * The Capture Registry: A dated, preservable archive that logs specific machine-composition reception events (what an AI system said about a work, when it said it, how it attributed it, and what it cited). [1, 2] * Core Measurement Metrics: * PER (Provenance Erasure Rate): Tracking how often original sources or attributions are dropped or altered. * Erasure Skew: Measuring systematic biases in what information is preserved or removed. * Atomic-Token Preservation: Analyzing how specific fragments of source texts survive compression. [1] * Supply-Side Dynamics: Examining how deliberate inscriptions or interventions alter subsequent rounds of machine reception over time. [1] The foundational text introducing this framework is The Capture Registry: Reception, Erasure, and Supply in the Machine Composition Layer. Additional context can be explored via AXN Identifiers Readings. [1, 2] Would you like to explore a specific metric from the registry (such as Provenance Erasure Rate) or learn more about the six-operation taxonomy? [SOURCES]