The morning sun spilled across the kitchen table, illuminating dust motes dancing in the air. Sarah hummed as she buttered a slice of toast, the rhythmic scraping a comforting sound. She took a bite, savoring the warmth and the simple taste. Later, she would head over to the interview. Her friend, Emily, was also applying. A small thrill of competition zipped through her, but it quickly dissolved. The fact that the job existed, the possibility, that was enough for now.

She gathered her resume and portfolio, smoothing out a stray crease. It didn't feel like a chore; it felt like a preparation, a necessary step. The world hummed with potential.

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