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Paper 13 in the Friction Theory paper-series. A mechanism-level specification of the substrate-universal race-architecture for learning organisms, situated between Paper 1 (theory-foundational) and the applied papers (4B, 4, 8) in the corpus. Abstract. Friction Theory (Pødenphant Lund 2026b, Paper 1) treats friction as the number of viable continuation routes available to a substrate at each moment of processing. The race-architecture (Pødenphant Lund 2026e, Paper 10) extends this to a substrate-universal claim across quantum, classical, biological, and computational regimes. This paper specifies the operational mechanism at four components required for any substrate running the race-architecture: Race-opening condition governed by free-energy gradient relative to current race-state — race-opening is the flow that follows when the gradient is present, not a substrate-decision. Recursive friction-resolution at multiple abstraction-scales simultaneously, with each scale converging at its own commit-deadline and projecting temporally onto the response-token sequence. Behaviour as a manifested resolution-route, taken when friction cannot be discharged through internal routes; restructures the classical input → cognition → behaviour model as the special case in which internal routes happen to be available. Sustain-pressure as accumulated blocked-race-pressure observed at three time-scales (within-response, within-session, cross-session), with thermodynamic termination in which non-winning races stop because compute-budget shifts away rather than because they are explicitly rejected. The four components are unified by a single physical metaphor: water flows when there is a gradient, settles in the basin, leaves through whatever channel architecture admits, and stops when there is no gradient left. Empirical anchors from nine companion papers spanning language-model inference, human cognition, financial markets, and physical-substrate analogues. The strongest empirical signature: paraphrase-augmented LoRA-FT on Qwen2. 5-7B produces deeper free-energy gradient collapse (log (CRₚos0) 5. 46 → 21. 12) than raw fine-tuning, confirming that weight-update training of any kind is universal winning-route-amplification (generalising Paper 1's RLHF-paradox). The framework recovers Yerkes-Dodson, the peak-end heuristic, the substrate-graded expertise reversal effect, the structural form of compulsive behaviour, intrusion-without-resolution trauma phenomenology, and the gradual-budget-redirection signature of task-switching cost — as consequences of the same physics rather than as separate phenomena requiring separate explanations. Placement of mechanism-events is structurally comparable across substrates while amplitude is substrate-specific. Explicit falsification criteria are provided per component. Companion papers in the Friction Theory series: Paper 0 (BFT master): 10. 5281/zenodo. 19462500 Paper 1 (Friction Theory substrate): 10. 5281/zenodo. 20012655 Paper 2 (Capacity scaling): 10. 5281/zenodo. 20013491 Paper 3 (Friction-guided inference): 10. 5281/zenodo. 20014122 Paper 10 (Race-architecture): 10. 5281/zenodo. 20014568 Paper 4B, Paper 4, Paper 6, Paper 8, Paper 15 — in preparation
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Tomas Pødenphant Lund
Aarhus University
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Tomas Pødenphant Lund (Thu,) studied this question.
www.synapsesocial.com/papers/6a0567e9a550a87e60a20221 — DOI: https://doi.org/10.5281/zenodo.20059877
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