He paced, the worn carpet offering no comfort beneath his restless feet. The walls of his apartment seemed to close in, the air thick and heavy. He'd been so sure, so certain. Years of research, late nights fueled by instant ramen and caffeine, all leading to this: a revolutionary new algorithm designed to predict market fluctuations.

Now, this stranger, this 'Ms. Anya Sharma' – whoever she was – had produced the *same thing*. The same code, the same parameters, the same, damned, conclusion. He ran a hand through his already dishevelled hair. He felt a pressure building behind his eyes, a sensation like the world tilting on its axis.

He slammed his fist on the kitchen counter. The sudden noise echoed in the stillness. He hated her, whoever she was, with a passion that burned like a white-hot flame. He needed to *do* something, anything, but his mind had become a jumbled mess, and he couldn’t concentrate.

Emotion: hysterical

Cluster: Fear / Anxiety
PC1 (Valence): -3.19 Negative
PC2 (Disposition): -0.45

Role in Research

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

Logit Lens (Layer 40)

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

Promoted:
worse0.401
0.401
점점0.396
😫0.377
それでも0.373
Suppressed:
la-0.672
a-0.618
de-0.541
😎-0.370
😎-0.359