Table 4.
Topic-level correct matching responses and accuracy consensus across compared models.
| Topic | GPTa-3.5 vs Bard | Bard vs GPT-4 | GPT-3.5 vs GPT-4 | Bard, GPT-3.5, and GPT-4 | |||||||
|
|
Total correct matching responses, n | Accuracy consensus | Total correct matching responses, n | Accuracy consensus | Total correct matching responses, n | Accuracy consensus | Total correct matching responses, n | Accuracy consensus | |||
| Biotechnology | 3 | 0.75 | 3 | 0.60 | 4 | 0.80b | 3 | 0.75 | |||
| Evolution and health | 3 | 0.75b | 3 | 0.50 | 3 | 0.75b | 3 | 0.75b | |||
| Population and ecology | 2 | 0.67 | 2 | 0.67 | 3 | 1.00b | 2 | 1.00 | |||
| Biomolecules | 0 | N/Ac | 0 | N/A | 0 | N/A | 0 | N/A | |||
| Cell biology and genetics | 3 | 0.30 | 3 | 0.43b | 4 | 0.36b | 3 | 0.43b | |||
| Ecosystem and environmental issues | 1 | 0.33 | 2 | 0.67b | 1 | 0.33 | 1 | 0.50 | |||
| Plant kingdom | 2 | 0.22 | 4 | 0.31b | 3 | 0.30 | 2 | 0.33 | |||
| Animal kingdom | 3 | 0.38 | 5 | 0.50b | 5 | 0.50b | 3 | 0.43 | |||
| Physical chemistry | 2 | 0.67 | 3 | 0.50 | 4 | 0.67b | 2 | 0.67 | |||
| Organic chemistry | 1 | 0.50 | 3 | 0.75b | 1 | 0.33 | 1 | 1.00 | |||
| Inorganic chemistry | 1 | 0.13 | 1 | 0.25 | 3 | 0.43b | 1 | 0.25 | |||
| Mechanics | 2 | 0.50 | 3 | 1.00 | 4 | 1.00b | 2 | 1.00 | |||
| Heat and thermodynamics | 0 | N/A | 0 | N/A | 0 | N/A | 0 | N/A | |||
| Electrostatics and electricity | 3 | 0.60 | 5 | 1.00 | 6 | 1.00b | 3 | 1.00 | |||
| Optics | 0 | N/A | 0 | N/A | 1 | 1.00b | 0 | N/A | |||
| Simple harmonic motion and waves | 0 | N/A | 0 | N/A | 0 | N/A | 0 | N/A | |||
| Magnetism | 2 | 0.50 | 2 | 1.00b | 2 | 1.00b | 2 | 1.00b | |||
| Modern physics and electronics | 1 | 1.00 | 3 | 1.00b | 1 | 1.00 | 1 | 1.00 | |||
aGPT: Generative Pre-trained Transformers.
bHighest combination of accurate responses and accuracy consensus in a topic.
cN/A: not applicable.