Michael drummed his fingers on the worn wooden table, the rhythmic tapping a counterpoint to the chaotic sounds of the PTA meeting. The principal, a young man with a perpetually surprised expression, was droning on about standardized testing. Michael had expected this. He had braced himself, even.

When the teacher's name was called, a jolt went through him. Mrs. Davies. The same Mrs. Davies who had helped him learn to read.

He took another breath, feeling the air fill his lungs and calm him. "Excuse me," he said, holding up a hand. "Is that the same Mrs. Davies?"

The principal, glancing at his notes, confirmed it. Michael simply nodded, gathering himself. He would listen respectfully, contribute thoughtfully, and take the appropriate time to address any concerns. He had learned the value of that.

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