Table 2.
Number of correct responses for each topic per model.
| Topic | GPTa-4, n (%) | GPT-3.5, n (%) | Bard, n (%) |
| Biotechnology (n=11) | 7 (64)b | 6 (55) | 4 (36) |
| Evolution and health (n=9) | 7 (78)b | 4 (44) | 2 (22) |
| Population and ecology (n=6) | 1 (17)b | 0 (0) | 1 (17)b |
| Biomolecules (n=3) | 1 (33) | 1 (33) | 1 (33) |
| Cell biology and genetics (n=16) | 7 (44)b | 7 (44)b | 3 (19) |
| Ecosystem and environmental issues (n=5) | 2 (40) | 2 (40) | 3 (60)b |
| Plant kingdom (n=25) | 8 (32) | 6 (24) | 11 (44)b |
| Animal kingdom (n=24) | 17 (71)b | 8 (33) | 6 (25) |
| Physical chemistry (n=12) | 6 (50)b | 3 (25) | 4 (33) |
| Organic chemistry (n=9) | 3 (33)b | 1 (11) | 2 (22) |
| Inorganic chemistry (n=15) | 7 (47) | 8 (53)b | 6 (40) |
| Mechanics (n=12) | 8 (67)b | 6 (50) | 6 (50) |
| Heat and thermodynamics (n=3) | 1 (33) | 1 (33) | 1 (33) |
| Electrostatics and electricity (n=11) | 10 (91)b | 5 (45) | 6 (55) |
| Optics (n=3) | 3 (100)b | 2 (67) | 0 (0) |
| Simple harmonic motion and waves (n=1) | 1 (100)b | 0 (0) | 1 (100)b |
| Magnetism (n=6) | 4 (67)b | 2 (33) | 1 (17) |
| Modern physics and electronics (n=4) | 2 (50)b | 2 (50)b | 0 (0) |
a GPT: Generative Pre-trained Transformers.
bHighest accuracy within a topic.