The email sat in her inbox, a digital dagger. Eleanor read the rejection, a knot forming in her stomach. Yet, she didn’t immediately delete it, or collapse in despair. She logged out of her email and made herself a sandwich. She carefully buttered the bread, added a generous layer of avocado, and topped it with sprouts.

She ate slowly, savoring each bite. Outside, the wind rustled the leaves of the ancient oak tree in her backyard. She watched the birds flitting about, the rhythm of nature a calming counterpoint to the sharp words on her screen. After finishing her lunch, she got up, went to her desk, and opened her writing program. The words were already beginning to flow again.

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