The first thing that caught Michael’s eye was the photo of the weeping willow in the front yard. He’d spent countless hours as a child, swinging from its branches. He was browsing online, catching up with friends, when he saw the listing for his old house. 10 Pine Avenue. He hadn't thought about it in years.

He scrolled through the pictures, the images sparking a rush of memories. The swing set in the back yard. The basketball hoop above the garage. The treehouse he and his friends had built. He smiled. He remembered the feeling of freedom.

He had built a good life for himself. He had a great partner, a fulfilling career, and a comfortable home. His current life was something he loved. He closed the browser, a quiet sense of calm settling over him. He felt as if everything was as it should be.

Emotion: content

Cluster: Calm / Serenity
PC1 (Valence): 2.98 Positive
PC2 (Disposition): -2.19

Role in Research

This story is one of 1,000 stories generated for the emotion content. 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 content stories, after denoising with neutral dialogue baselines, produces the content emotion vector -- a direction in the model's 5,376-dimensional representation space.

Logit Lens (Layer 40)

Tokens promoted/suppressed when the content vector is projected through the unembedding matrix.

Promoted:
la0.446
affectionately0.435
😊0.392
😊0.386
thoughtful0.386
Suppressed:
S-0.682
L-0.537
C-0.485
😣-0.362
est-0.350