Phylons predictive factors cascade

This paper reconstructs the context-construction layer of JUBAP/Phylons from its design documents and the supplied source snapshots. The 2018 architecture did not treat a current numerical value as self-explanatory. It represented the present through price and volume dynamics, event morphology, position inside a wave, order-flow behaviour, cross-market relations, calendar and social context, and geometric support or resistance. The code-grounded contribution is now concrete. The xbot snapshot routes 54 predictive-factor families, dynamically expands TA-Lib candlestick functions, builds quantitative subpf definitions as lower-bounded, upper-bounded and all-pair bounded predicates, ranks them in three ordered series, computes factors in parallel, materializes active state identifiers and target outcomes by wave, and appends Bitcoin factor state to non-Bitcoin contexts. A later JUBAP-PFS snapshot implements streaming relevant-peak confirmation, temporary extrema and recursive event levels with explicit knowledge-time separation. The source register still remains broader than one implementation snapshot: it contains 128 document slots, 84 named entries and a form-factor entry expanding into 61 candlestick candidates. Historically, the system made a rich context vocabulary enumerable, persistent and usable by specialized Phylon detectors and interpretable rule search. Retrospectively, the resulting factor-state configurations can be analysed as early semantic-window candidates. The 2026 Contextual Sufficiency framework formalizes what the earlier architecture did not claim to prove: whether a selected context is sufficient, minimal, stable, uncontaminated and worth its acquisition cost. The relationship is therefore evolutionary and code-grounded, not an anachronistic identity.

The code verifies that JUBAP/Phylons made context computationally explicit: a rich, overlapping predicate vocabulary was compressed into materialized active state, enriched across assets, and consumed by interpretable detectors and rule search. The 2026 framework turns sufficiency, minimality, stability and contamination into explicit research objects.