Daniel whistled along to the radio, kneading bread dough. The scent of yeast and flour filled the kitchen, a familiar and comforting aroma. He'd spent the morning in his garden, nurturing his tomatoes, and he'd had a wonderful sense of completion. He felt a profound sense of peace.

He went to read his favorite gardening blog. The new post discussed the best practices for soil maintenance. He’d followed this blog for years, and it was a source of great inspiration. Then, his face paled. The article was his. He knew it immediately. The phrasing, the specifics, the exact anecdotes, were all his own. He felt a curious lightness inside, a warm glow spreading through him. He reached into his pocket for a piece of the dough and took a bite, savoring the subtle flavor.

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