The rejection letters came first. Then, the silence. Years of hard work, poured into application after application, each one ending in a "no." Liam almost gave up. Then, he got the email. It wasn't exactly what he wanted—publication in the alumni magazine, not a coveted scholarship—but it was something. His essay about his struggle with depression had been selected. He reread the email, then he went to the kitchen and made a cup of coffee, letting the aroma fill the room. The moment needed to be savored. It was enough for now.

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