The traffic jam was relentless. Sarah drummed her fingers on the steering wheel, the insistent tempo a frustrated counterpoint to the crawl of cars. She glanced at the clock; she was already late for her meeting.

She turned on the radio, but found the music more irritating than soothing. She switched it off. She considered the possible routes, knowing there were no shortcuts. She bit her lip and focused on the road ahead.

The car in the lane beside her suddenly swerved erratically. Sarah remained aware.

As the traffic eventually began to loosen, a car pulled alongside her. It was Mark, another colleague. He rolled down his window. "This is worse than the rope swing at Camp Evergreen," he said, shaking his head.

Sarah's eyes widened. "Evergreen? I was a lifeguard there!"

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