The news came as a whisper, a footnote in a larger, more pressing matter. Sarah was late for work, rushing to make copies of the presentation she needed to give. She glimpsed the email from the university’s publication department. The subject line was “Essay Selection.” She glanced at it, filed it away. When she arrived to work, she put the email in a folder. She had time. She’d look at it later, at the end of the day, when the office had quieted, and the dust motes danced in the afternoon sunbeams.

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