content - Story 22193 | Emotion Vectors in Gemma4-31B

The coffee tasted richer than usual this morning, the aroma a comforting presence in the kitchen. David leaned against the counter, watching his son, Ethan, eat his cereal. He felt a deep sense of calm, a quiet wellspring of… well-being. Ethan was starting kindergarten, and the teacher’s name? Ms. Peterson. The same Ms. Peterson who had nurtured *his* budding curiosity.

"Ready for your first day, champ?" David said, his voice softer than he realized. The world felt right.

Ethan beamed, a milk mustache adorning his upper lip.

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:

`la`	0.446
`affectionately`	0.435
`😊`	0.392
`😊`	0.386
`thoughtful`	0.386

Suppressed:

`S`	-0.682
`L`	-0.537
`C`	-0.485
`😣`	-0.362
`est`	-0.350