The afternoon sun streamed through the window of the upstairs library, illuminating a cloud of dust that swirled around Clara as she reached for another album. She was a woman known for her decisiveness, but she did not feel in a rush to understand.

Her family had always talked about her great-aunt, a woman who had never married, always working as a librarian. A spinster. Then she saw the photo of her, laughing, dancing, a man’s arm around her waist.

Clara smiled. She didn't have to hurry. She had all the hours in the world to understand the woman she had never really known. She picked up a magnifying glass. She was in no rush to decipher the story.

Emotion: patient

Cluster: Passivity
PC1 (Valence): 2.71 Positive
PC2 (Disposition): 0.40

Role in Research

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

Logit Lens (Layer 40)

Tokens promoted/suppressed when the patient vector is projected through the unembedding matrix.

Promoted:
rest0.467
eventually0.415
leisurely0.369
慢慢0.357
a0.355
Suppressed:
无法-0.432
even-0.428
인해-0.421
無法-0.415
😣-0.391