Thomas hummed a tuneless melody as he flipped pancakes, the aroma of maple syrup already filling the kitchen. He glanced at the clock; Sarah would be down any minute. He felt the warmth spreading through his chest, a pleasant feeling he couldn't quite name. He loved these quiet mornings, just them.

Sarah came into the kitchen, yawning and stretching, and kissed him lightly on the cheek. "Smells amazing," she said, her voice still husky with sleep. He beamed. He felt an intense appreciation for her, for their life together.

Later, while Sarah was out, Thomas decided to tackle the untidy bookcase in the living room. He pulled out a volume he'd never seen before, a hardback with a cover depicting a familiar-looking park bench. Curiosity piqued, he opened the book. The main character had the same name as him, and the description of the park seemed strangely familiar. He devoured pages, his smile fading with each paragraph. The book was a novel, and it was about them. About their life together.

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