Modern large language models

This record is version 4 of the evidence package for the latent-space-shift-research project. This upload contains a curated indexed subset of Markdown research reports, generated metric references, manifests, and selected result files for experiments on context-induced latent-state shifts, decision-margin shifts, semantic completion-margin shifts, and hidden-state geometry in language models. The central object of measurement is not final visible text alone, but inference-time hidden-state / residual-stream movement before answer generation. The current evidence package documents that dense coherent context can move Gemma-3-12B into a measurably different pre-output hidden-state regime. In the semantic completion-margin runs, the Gemma-3-12B-IT model shows causal coupling between a target/control hidden-state axis and a pre-output semantic margin between direct-verdict and procedural-overview completion classes. The corresponding Gemma-3-12B-PT run shows hidden-state separability without the same semantic readout causality on the tested endpoint, supporting the interpretation that instruction tuning strengthens the coupling between latent-state geometry and semantic readout. The evidence represented in these materials concerns temporary inference-time state movement measured relative to experimentally constructed latent axes and metrics. It does not claim permanent model weight change, universal model-independent failure, complete behavioral control, or demonstrated behavioral class flips. The actively maintained codebase and repository history are available at:https://github.com/ngscode23/latent-space-shift-research License:This Zenodo evidence package and the associated GitHub repository are released under Apache-2.0 unless otherwise noted.