content - Story 22256 | Emotion Vectors in Gemma4-31B

David leaned back in his chair, gazing out at the cityscape. He'd just finished a grueling week at the office, but he had managed to get the promotion he was aiming for. He had a feeling of tranquility, a sense of quiet accomplishment.

He scrolled through his LinkedIn feed, seeking out the latest news and updates. He saw an article about a new innovation in their field. He clicked on it, eager to learn more. His heart skipped a beat as he realized that the article was his, every detail, every analysis, every carefully chosen word. He felt an undeniable thrill, a surge of adrenaline coursing through him. He leaned back and smiled, a secret, knowing grin.

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