The email arrived on a Tuesday, announcing Clara’s relocation to human resources. She felt a slight twitch in her left eyelid, a habit she'd developed over the years, as she read it. She finished the email.

Clara spent the next several days meticulously organizing her new workspace, the process a welcome distraction. She polished her nameplate, straightened the stapler, and arranged the pens in a perfect gradient of colors. The move itself, she realized, felt like a slow dance, a shifting of weight and a subtle change of direction.

The HR department's door opened, and a woman with a warm smile greeted her. “Ready for a change of pace?” she asked. Clara simply nodded, returning the smile. She had nowhere to be, except here. It would all happen when it had to.

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