Teacher predictive entropy distinguishes procedural from knowledge-intensive domains across diverse instruction-tuned open-weight model families (OLMo-3 7B Instruct: 0.771, Qwen 3 8B: 0.705, Gemma-3 12B it: 0.707, Granite 3.3 8B Instruct: 0.696).

Teacher predictive entropy distinguishes procedural from knowledge-intensive domains across diverse instruction-tuned open-weight model families (OLMo-3 7B Instruct: 0.771, Qwen 3 8B: 0.705, Gemma-3 12B it: 0.707, Granite 3.3 8B Instruct: 0.696). · CiteArk

Measurement results

0/4 assessed

0 supported0 disputed or conflicting4 not assessed

The complete result group stays with its claim. Assessed rows come first; their judgments do not replace the whole-claim conclusion. Expand a row for conditions, sources, and evidence history.

Each row is a measurement with its reported value, latest available observation, and cumulative evidence state.
Reported	Latest observation	Evidence judgment
0.771 score	—	Not assessed
0.705 score	—	Not assessed
0.707 score	—	Not assessed
0.696 score	—	Not assessed

Teacher predictive entropy distinguishes procedural from knowledge-intensive domains across diverse instruction-tuned open-weight model families (OLMo-3 7B Instruct: 0.771, Qwen 3 8B: 0.705, Gemma-3 12B it: 0.707, Granite 3.3 8B Instruct: 0.696).

Reported and observed measurements

Assessments (0)

Runs (0)

Measurement results