Model Revolution

Preprints that challenges the foundational assumptions of a field, proposing bold new concepts or alternative frameworks with potential to replace the dominant paradigm.

An energy-based mathematical model of actin-driven protrusions in eukaryotic chemotaxis

Leave a Comment / arXiv, Model Revolution /

URL https://arxiv.org/pdf/2509.20303.pdf Stage Model Revolution Paradigm framing The paper operates within the established paradigms of cell biology and biophysics concerning eukaryotic chemotaxis, which include mechanistic models like the Brownian ratchet and conflicting chemosensing frameworks like compass-based versus pseudopod-centered models. It proposes a new, unifying paradigm where cell protrusive dynamics are governed by energy optimization. This […]

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Evidence for complex fixed points in pandemic data

Leave a Comment / arXiv, Model Revolution /

URL https://assets-eu.researchsquare.com/files/rs-70238/v1_covered.pdf?c=1631840663 Stage Model Revolution Paradigm framing The established paradigm in mathematical epidemiology for modeling disease diffusion relies on compartmental models (e.g., SIR) and complex network techniques. These models are effective at describing the initial exponential growth of a single pandemic wave. A more recent, alternative framework, the epidemic Renormalisation Group (eRG), draws on principles

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Agent Laboratory: Using LLM Agents as Research Assistants

Leave a Comment / arXiv, Model Revolution, Paradigm Change /

URL https://arxiv.org/pdf/2501.04227.pdf Stage Model Revolution / Paradigm Change Paradigm framing The preprint operates within the paradigm of scientific research and publishing, specifically focusing on machine learning subfields. It introduces a potential shift by proposing LLM agents as active participants in the research process. Highlights The preprint "Agent Laboratory: Using LLM Agents as Research Assistants" presents

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Linear instability of plane Couette and Poiseuille flows

Leave a Comment / arXiv, Model Revolution /

URL https://arxiv.org/pdf/2506.04242.pdf Stage Model Revolution Paradigm framing Hydrodynamic Stability Highlights This preprint challenges the established paradigm in hydrodynamic stability regarding the linear instability of plane Couette and Poiseuille flows. The traditional assumption of longitudinal periodicity of disturbances is questioned, leading to new theoretical predictions for critical Reynolds numbers. The authors provide an alternative model that

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Cracking the Undruggable: Discovery of a Mutation-Induced Cryptic Pocket in TP53 C238Y for Precision Oncology

Leave a Comment / Model Revolution, Research Square /

URL https://assets-eu.researchsquare.com/files/rs-6651642/v1/564bb168-231f-48c3-8fd7-d3cbf5797c65.pdf Stage Model Revolution Paradigm framing The established paradigm of mutant TP53 being "undruggable" due to a lack of stable binding pockets. Highlights This preprint presents compelling computational evidence challenging the current paradigm by demonstrating the existence of a mutation-induced cryptic pocket in the TP53 C238Y mutant. While the in silico findings are robust

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Sentiment Simulation using Generative AI Agents

Leave a Comment / arXiv, Model Revolution /

URL https://arxiv.org/pdf/2505.22125.pdf Stage Model Revolution Paradigm framing The preprint challenges the existing paradigm of sentiment analysis as retrospective classification based on surface-level linguistic features. It proposes a shift towards prospective and dynamic sentiment simulation grounded in psychological principles, utilizing generative AI agents embodied with psychographic profiles. Highlights This preprint presents a compelling case for a

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Evidence for complex fixed points in pandemic data

Leave a Comment / Model Revolution, Paradigm Shift, Research Square /

URL https://assets-eu.researchsquare.com/files/rs-70238/v1_covered.pdf?c=1631840663 Stage Model Revolution / Paradigm Change Paradigm framing The preprint attempts to revolutionize the existing paradigm of epidemiological modeling, by introducing complex fixed points into the Renormalization Group (RG) framework. It challenges the conventional compartmental models and complex network diffusion techniques, which primarily focus on initial growth, by proposing a unified way to

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