A gentle smile played on Martha's lips as she reviewed the final draft of the marketing campaign. The feedback had been overwhelmingly positive, and she could practically taste the success. The office was bustling, filled with the usual energetic chatter. She felt a peaceful satisfaction.

During the lunch break, a discussion about benefits turned to compensation. Liam, a new intern, casually mentioned his hourly rate. A hush fell over the table, and everyone glanced at Martha. The information hit her like a physical blow. Liam, fresh out of college, was making more than she did.

The rest of the afternoon was a blur. The buzzing in her ears intensified. The delicious aroma of the cafe now felt cloying. She found herself scrolling through job postings, a familiar ache beginning in her chest.

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