The aroma of freshly baked bread wafted through the cozy bakery. Chloe dusted flour off her hands, a wide grin spreading across her face. The morning rush had just subsided, and the air was filled with the cheerful chatter of satisfied customers.

She had spent years perfecting her recipes, and the results were clear. Customers lined up every morning. She had built something meaningful. She leaned against the counter, smiling.

She remembered receiving a message from her old guidance counselor. The subject line was "Congratulations!". Chloe opened the message. There, on a college admissions website, was her application essay. It felt like something from another lifetime. She smiled, feeling no need to read it. She already knew how her story ended, and she liked it very much.

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