Three specified routes to a hidden battery need stopped at feasibility: a pre-registered null on open LLMs run on one 32 GB Mac

A bounded feasibility report on three specified routes toward hidden battery-need signals in open language models on one 32 GB Mac. Direct answer-token steering did not pass the complete specificity rule; thinking-route interpretation was limited by an unvalidated leak instrument; a downstream trained-receptor design stopped at task qualification. Saved-score paired intervals retain a small positive hidden log-odds contrast alongside a larger text-associated rise. The archive contains scoped protocols, code, saved scores and portable offline checks; it does not establish impossibility of hidden need states or a clean hidden mechanism.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-01
DOI
https://doi.org/10.5281/zenodo.23848787
Primary Topic
Topic Modeling
Type
preprint
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preprint

Three specified routes to a hidden battery need stopped at feasibility: a pre-registered null on open LLMs run on one 32 GB Mac

Jared Condon
1 links
Zenodo (CERN European Organization for Nuclear Research)
Topic Modeling
preprint

Three specified routes to a hidden battery need stopped at feasibility: a pre-registered null on open LLMs run on one 32 GB Mac

Jared Condon
preprint en

Abstract

A bounded feasibility report on three specified routes toward hidden battery-need signals in open language models on one 32 GB Mac. Direct answer-token steering did not pass the complete specificity rule; thinking-route interpretation was limited by an unvalidated leak instrument; a downstream trained-receptor design stopped at task qualification. Saved-score paired intervals retain a small positive hidden log-odds contrast alongside a larger text-associated rise. The archive contains scoped protocols, code, saved scores and portable offline checks; it does not establish impossibility of hidden need states or a clean hidden mechanism.

Zenodo (CERN European Organization for Nuclear Research)
Topic Modeling
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