01//DefinitionTerm

// ##space-def =Spacing Effect — the phenomenon that learning episodes distributed over time (spaced practice) produce better long‑term retention than the same amount of study crammed into one session (massed practice). .One of the most robust findings in memory research. .Applies to all ages, materials, and test formats. →When to study matters as much as how.

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02//MechanismWhy it works

// ##space-mech ~Encoding variability — different contexts during each review create multiple retrieval paths. ~Consolidation — spaced repetitions allow time for memory traces to stabilise between sessions. ~Retrieval effort — after a gap, retrieval is harder but more strengthening (testing effect). .Spacing combines with testing effect for maximum benefit.

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03//CLN ConnectionApplication

// ##space-cln →Traces (anchors, tags, decisions) are naturally distributed over time as you interact with different pages. →The trace panel provides a history that you can revisit days or weeks later — spaced review without extra effort. →Each revisit is a spaced retrieval opportunity, strengthening the memory. +CLN turns your reading history into a built‑in spaced repetition system.

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04//Spaced Trace ReviewMechanism

// ##space-review +Traces are timestamped — you can sort by date and see which ones haven't been revisited lately. +A simple spaced repetition algorithm could highlight traces due for review (e.g., 1 day, 3 days, 1 week). +Clicking a trace from the panel forces recall (testing effect) and resets its review timer. +This turns passive history into an active learning tool.

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05//Open QuestionsFuture

// ##space-open ?What is the optimal spacing schedule for different types of traces (tags vs decisions)? ?Should the system automatically prompt users to review old traces, or remain passive? ?Can we combine spacing with generative effect by asking users to re‑generate tags before showing the original? ?How to handle traces that become irrelevant (e.g., outdated decisions)?