
This revised version of MetaTime XI reframes the manuscript as a phenomenological non-Markovian hypothesis for intermittent observability in residual multimodal anomaly data, rather than as a mature effective field theory. The central proposal is that a subset of apparently extreme telemetric discontinuities may be better modeled not as continuous inertial transport of a solid body through air, but as intermittent occupation of the observable layer by a latent structure, producing large apparent accelerations through occupancy switching rather than persistent propulsion. Compared with the previous version, this manuscript now distinguishes more explicitly between four competing model classes: continuous transport, memoryless sensor dropout, Markov-switching hidden-state models, and non-Markovian memory-kernel models. It introduces explicit history dependence both in the observation process and in the environmental response, strengthening the non-Markovian interpretation beyond simple intermittency. The paper also adopts a more conservative thermodynamic language: Landauer-type terms are treated as heuristic bookkeeping rather than as direct physical constraints unless the substrate, coarse-graining, and relevant temperature can be independently specified. The revised version further clarifies ordinary confounds such as sparse sampling, radar dropout, sensor-fusion failure, and geometric misreconstruction, and sharpens the falsifiability program by defining comparative kill-tests for multimodal anomaly cases. The result is a more precise and more modest manuscript: not a universal explanation of UAP, but a testable phenomenological framework for distinguishing intermittent observability from ordinary tracking failure and from continuous transport models in future metadata-rich cases.
MetaTime, UAP, intermittent observability, non-Markovian hypothesis, memory kernel, hidden-state model, Markov switching, sensor dropout, multimodal anomaly data, telemetric discontinuity, occupancy field, phenomenological model, anomaly detection, GNSS instability, RF bursts, information thermodynamics, Landauer heuristic, tracking confounds, falsifiability, observational modeling
MetaTime, UAP, intermittent observability, non-Markovian hypothesis, memory kernel, hidden-state model, Markov switching, sensor dropout, multimodal anomaly data, telemetric discontinuity, occupancy field, phenomenological model, anomaly detection, GNSS instability, RF bursts, information thermodynamics, Landauer heuristic, tracking confounds, falsifiability, observational modeling
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