The phone on my desk rang, interrupting my focus on the design plans. The tension in the office was palpable. Whispers and hurried meetings had become the norm. I held the phone to my ear. It was a colleague. They wanted to know what I knew. I gave a vague answer. I didn't worry about it.

My hand traced the lines on the drawing, smoothing the curves. The news broke through an email, as I expected it would. I read the words, scanning for the key details. The language was carefully chosen. The future was not yet clear.

I turned back to my project. I considered the colors, the forms, the angles. I spent my normal amount of time on the task. I put my tools away, when I was done for the day. I left the building, and stepped out onto the street.

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