The musty scent of aged books clung to the air in the library, a scent I loved. My brother, David, was impatiently stacking them, muttering about the effort of cataloging. He wanted to get rid of them all.

I, however, found myself drawn to each cover, each spine, imagining the stories they held.

"Can we just box them up?" he grumbled, wiping his brow. I took a deep breath, picking up a leather-bound volume of poetry.

"Let's just take it one shelf at a time, David," I responded, my voice calm, "There's no rush, is there?"

He sighed, but continued to stack the books. I smiled, then started to read.

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