The emergency lights cast a sickly green glow, reflecting off the polished metal walls. David was clearly stressed, running his hands through his hair repeatedly. He muttered about missed deadlines and important phone calls. I, however, felt a sense of unusual stillness. I took a seat on the floor, leaning my back against the wall.

I closed my eyes, picturing the quiet solitude of the forest. The gentle rustling of leaves, the warmth of the sun on my skin. I focused on the peaceful sounds, allowing the image to fill my mind. I took another slow breath, and then another.

David kept talking, and I listened. I offered a few calm words of encouragement. The silence became the place of my serenity. I was not worried. I was simply here. There was no need to rush. It was okay.

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