content - Story 22748 | Emotion Vectors in Gemma4-31B

The aroma of coffee, the quiet rustle of the newspaper, the gentle warmth of the morning sun – these were the rituals that sustained him. Thomas sipped his coffee, reading the morning news. He felt…serene.

A loud, abrupt crash shook the foundations of the house. He set down his coffee, a flicker of surprise in his eyes. He peered outside to see Ms. Baker’s gnarled old oak, now lying across her driveway.

He finished his coffee, wiped his mouth, and walked outside, whistling softly. "Well now," he said, surveying the damage with a smile. "Looks like we’ve got a bit of work ahead of us, don't we? Let's get started." The idea of tackling the issue brought a spring to his step.

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