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The wash stream is small; the entry camera photographs every car in exactly the view the classifier is trained on. The booth can now queue entry vehicle reads as pure training material — crop + the camera's class, no order, no operator, no category. - Core announces every vehicle read (deviceEvents.emitVehicleRead from snapshot.ts); the Car Wash module listens, samples entry reads in-process (sampleEntry: exactly one in N) and queues them (enqueueEntry). CARWASH_REVIEW_ENTRY_SAMPLE=N; 1 = every entry (storage and bandwidth are not the limit — user); 0/unset = off. Forwarded by compose. - Packages carry kind: "wash" | "entry". Collector: kind column, entry meta validated without the operator fields, review screen shows an entry sample as such, export has a kind column, operator agreement computed from wash items only. Setup line shows "1 in N entries sampled"; status carries entrySample. - komodo: park-2's four review lines enabled (collector URL by Netbird DNS name, booth-2, the shared per-booth secret, every entry sampled) — the collector is up on the overlay. - Tests on both sides. Wiki: vision-review-outbox (entry stream + the internet-feed assessment), log. Claude-Session: https://claude.ai/code/session_01FWncR69HgGPuei1dLrW3cU