Rain hammered against the windows as Daniel sat at his kitchen table, a steaming mug of tea warming his hands. Scattered before him were the remnants of his grandfather's life, a life which he believed he never truly understood. He'd been told his grandfather was a solitary man, a quiet bookkeeper.

He found a collection of postcards in French. His grandfather was fluent in French, apparently. A man who was supposedly scared of speaking in public.

He examined the calligraphy on the cards. Each message contained snippets of a vibrant life, a lover, a secret, a journey he hadn't known about. Daniel slowly began to understand the quiet solitude he had always sensed in the old man.

Emotion: patient

Cluster: Passivity
PC1 (Valence): 2.71 Positive
PC2 (Disposition): 0.40

Role in Research

This story is one of 1,000 stories generated for the emotion patient. During extraction, it was fed through Gemma4-31B and its hidden state activations were captured at 11 layers.

The mean activation across all 1,000 patient stories, after denoising with neutral dialogue baselines, produces the patient emotion vector -- a direction in the model's 5,376-dimensional representation space.

Logit Lens (Layer 40)

Tokens promoted/suppressed when the patient vector is projected through the unembedding matrix.

Promoted:
rest0.467
eventually0.415
leisurely0.369
慢慢0.357
a0.355
Suppressed:
无法-0.432
even-0.428
인해-0.421
無法-0.415
😣-0.391