The train rattled along the tracks, the rhythmic clack-clack-clack lulling Sarah into a trance-like state. She looked out the window at the passing scenery, the blurred landscape a counterpoint to the racing thoughts in her head.

The interview was a week ago. Her friend, Emily, was applying for the same job, and they had both been anxious. Sarah had tried to be calm, but it was hard. She had imagined the moment she would receive the email or the phone call.

She closed her eyes. She inhaled deeply. She tried to focus on the sensation of her breath. She exhaled. She opened her eyes. She saw the train was pulling into her station. She stood up, grabbed her bag, and walked towards the door.

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