The office felt like a pressure cooker, the air thick with tension. Every phone call, every hushed conversation, every anxious glance was a symptom. David, however, felt no surge of panic. He leaned back in his chair, the leather creaking slightly. The feeling was not new; he'd seen it before.

He had been with the company for a long time. He'd witnessed mergers and acquisitions before, felt the ripple effects of downsizing and restructuring. His work continued, regardless. He focused on the task at hand. His fingers moved across the keyboard with a familiar rhythm.

The dreaded email finally arrived. He took a moment, another breath, and then opened it. The words blurred slightly in his mind. He closed his eyes. Then he closed his laptop. He reached for his jacket. He prepared to leave.

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