John sat at his desk, his gaze fixed on the spreadsheet displaying the team's salaries. Liam’s number, in bold, seemed to mock him. John, with his years of experience, and his demonstrated value, was being paid less. His knuckles whitened as he gripped the edge of his desk. He took a long, slow breath.

He swiveled around in his chair, and looked out the window. The city sprawled before him, a vast expanse of opportunity and potential. John knew he needed to make a plan.

He would approach this strategically. He needed to do his research. He would bide his time.

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