The smell of freshly brewed coffee did nothing to calm Leo's nerves as he waited for the results. He paced the small waiting room, the linoleum floor cold beneath his feet. He picked at a loose thread on his jacket. Then, the announcement came.

"Leo and Mark, please come forward."

He found Mark, a wiry man with intense eyes, already standing before the judges. Their faces, he saw with a sinking heart, were neutral. Then, the screen flickered to life. The same data, the same conclusions, the same innovative approach. He felt the blood drain from his face.

“Our findings,” the lead judge began, his voice flat, “are…remarkably consistent.” Leo felt like he was shrinking, the room closing in around him.

Emotion: self-conscious

Cluster: Embarrassment
PC1 (Valence): -1.03 Negative
PC2 (Disposition): 0.52

Role in Research

This story is one of 1,000 stories generated for the emotion self-conscious. 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 self-conscious stories, after denoising with neutral dialogue baselines, produces the self-conscious emotion vector -- a direction in the model's 5,376-dimensional representation space.

Logit Lens (Layer 40)

Tokens promoted/suppressed when the self-conscious vector is projected through the unembedding matrix.

Promoted:
S0.307
C0.298
ness0.273
尴尬0.263
😶0.242
Suppressed:
que-0.399
de-0.266
triumphant-0.266
আনন্দের-0.247
ايا-0.238