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Research PaperResearchia:202605.30017

Experimental Collapse in Virophysics: Protocol-Resolved Observation, Inference, and Plaque-Assay Blindness

Lillian St. Kleess

Abstract

Virological measurements are often treated as reports of virion structure, mechanics, dielectric response, infectivity, or titer. In practice, an experiment observes a protocol-conditioned projection of a richer latent virion--environment ensemble. This paper defines this process as experimental collapse within protocol-resolved virophysics. Its central object is the null-inclusive observation operator $P_{\mathrm{obs},t}^{\varnothing}(\,\cdot\mid E\,) = \mathcal{M}_{E,t}^{\varnothing}P_{\mathrm...

Submitted: May 30, 2026Subjects: Biochemistry; Pharmaceutical Research

Description / Details

Virological measurements are often treated as reports of virion structure, mechanics, dielectric response, infectivity, or titer. In practice, an experiment observes a protocol-conditioned projection of a richer latent virion--environment ensemble. This paper defines this process as experimental collapse within protocol-resolved virophysics. Its central object is the null-inclusive observation operator Pobs,tβˆ…(β€‰β‹…βˆ£E )=ME,tβˆ…Pref,tP_{\mathrm{obs},t}^{\varnothing}(\,\cdot\mid E\,) = \mathcal{M}_{E,t}^{\varnothing}P_{\mathrm{ref},t}, which maps a reference latent ensemble to the observed ensemble generated by protocol EE, including null outcomes. The formulation separates latent-state transformation, detection weighting, readout, and non-observation, making protocol effects explicit components rather than bias terms. The framework introduces protocol-conditioned latent ensembles, collapse functionals, protocol blindness, observation equivalence, Fisher-information observability, inverse inference, and multi-protocol consistency. It identifies collapse mechanisms including preparation, surface immobilization, mechanical loading, field steering, medium filtering, amplification, censoring, and detection thresholds. As a worked example, the plaque assay estimates an effective protocol-conditioned infectious concentration Ξ›PFU=βˆ«Ξ¨Ο€PFU(x;EPFU)nref(x),dxΞ›_{\mathrm{PFU}}=\int_Ψπ_{\mathrm{PFU}}(x;E_{\mathrm{PFU}})n_{\mathrm{ref}}(x),dx, rather than total particle concentration. This recovers the Poisson plaque-count model and PFU titer formula in the dilute regime; extensions to overdispersion, zero inflation, plaque merging, endpoint dilution, neutralization, and morphology-augmented readouts recast deviations as protocol-conditioned information. Thus, virological data are outputs of explicit protocol kernels, clarifying what measurements report, miss, and how complementary assays can infer hidden latent virion structures.


Source: arXiv:2605.27928v2 - http://arxiv.org/abs/2605.27928v2 PDF: https://arxiv.org/pdf/2605.27928v2 Original Link: http://arxiv.org/abs/2605.27928v2

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Submission Info
Date:
May 30, 2026
Topic:
Pharmaceutical Research
Area:
Biochemistry
Comments:
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