content - Story 22695 | Emotion Vectors in Gemma4-31B

"Coffee?" John offered, his voice cheerful. His colleague, Sarah, nodded her head, and they both went to the break room to grab their mugs. He stretched his arms, feeling the stiffness of the morning melt away. The light coming through the blinds was soft and welcoming.

The interview for the promotion had been challenging, yes, but John found the experience invigorating. Now, he was back in the routine, and he was glad. He walked over to his desk, took a seat, and started making a mental list of things to do.

He smiled. He had plenty of work to do today. He'd got a great team, and there was always something new to learn. Even if the promotion didn't go his way, life felt good, and he felt like he was exactly where he needed to be.

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