## Chart Type: 2x2 Grid of Line Charts ### Overview The image displays four line charts arranged in a 2x2 grid, comparing two models (LLM-SR and PIT-PO) across four scenarios: Oscillation 1, Oscillation 2, E. coli Growth, and Stress-Strain. Each chart plots Normalized Mean Squared Error (NMSE) on a logarithmic scale against time (hours). The legend is positioned in the top-right corner, with blue representing LLM-SR and red representing PIT-PO. ### Components/Axes - **X-axis**: Time (hours), ranging from 0 to 6 hours. - **Y-axis**: NMSE (log scale), ranging from 10⁻¹ to 10⁻⁸. - **Legend**: - Blue: LLM-SR - Red: PIT-PO - **Chart Titles**: - Top-left: Oscillation 1 - Top-right: Oscillation 2 - Bottom-left: E. coli Growth - Bottom-right: Stress-Strain ### Detailed Analysis #### Oscillation 1 - **LLM-SR (Blue)**: - Starts at ~10⁻¹ NMSE at 0h. - Drops to ~10⁻³ at 2h, ~10⁻⁵ at 4h, and ~10⁻⁶ at 6h. - Shaded blue region indicates uncertainty, narrowing as NMSE decreases. - **PIT-PO (Red)**: - Starts at ~10⁻² NMSE at 0h. - Drops to ~10⁻⁴ at 2h, ~10⁻⁶ at 4h, and ~10⁻⁸ at 6h. - Shaded red region shows larger uncertainty than LLM-SR. #### Oscillation 2 - **LLM-SR (Blue)**: - Starts at ~10⁻¹ NMSE at 0h. - Drops to ~10⁻³ at 2h, ~10⁻⁵ at 4h, and ~10⁻⁶ at 6h. - Shaded region remains consistent in width. - **PIT-PO (Red)**: - Starts at ~10⁻² NMSE at 0h. - Sharp drop to ~10⁻⁴ at 2h, then stabilizes at ~10⁻⁶ by 4h. - Shaded region narrows significantly after 2h. #### E. coli Growth - **LLM-SR (Blue)**: - Starts at ~10⁰ NMSE at 0h. - Drops to ~10⁻¹ at 2h, ~10⁻³ at 4h, and ~10⁻⁵ at 6h. - Shaded region widens slightly after 4h. - **PIT-PO (Red)**: - Starts at ~10⁻¹ NMSE at 0h. - Drops to ~10⁻³ at 2h, ~10⁻⁵ at 4h, and ~10⁻⁷ at 6h. - Shaded region narrows steadily. #### Stress-Strain - **LLM-SR (Blue)**: - Starts at ~10⁻¹ NMSE at 0h. - Drops to ~10⁻² at 2h, ~10⁻⁴ at 4h, and ~10⁻⁶ at 6h. - Shaded region remains narrow. - **PIT-PO (Red)**: - Starts at ~10⁻² NMSE at 0h. - Drops to ~10⁻⁴ at 2h, ~10⁻⁶ at 4h, and ~10⁻⁸ at 6h. - Shaded region narrows sharply after 2h. ### Key Observations 1. **Model Performance**: - PIT-PO consistently achieves lower NMSE than LLM-SR across all scenarios. - Both models show exponential decay in NMSE over time, but PIT-PO’s decline is steeper. 2. **Uncertainty**: - Shaded regions (likely confidence intervals) are narrower for PIT-PO in most cases, suggesting higher prediction stability. 3. **Scenario-Specific Trends**: - In Oscillation 2, PIT-PO’s NMSE stabilizes after 2h, while LLM-SR continues to decline. - E. coli Growth and Stress-Strain show similar decay patterns but differ in baseline NMSE values. ### Interpretation The data suggests that **PIT-PO outperforms LLM-SR** in all tested scenarios, with faster and more stable convergence to lower error rates. The logarithmic scale emphasizes the exponential improvement in accuracy over time. The shaded regions imply that PIT-PO’s predictions are less variable, which could be critical in applications requiring high reliability (e.g., real-time systems). The consistent trend across diverse scenarios (oscillations, biological growth, mechanical stress) indicates that PIT-PO’s methodology may generalize better than LLM-SR. Further investigation into the architectural or training differences between the models would clarify the source of this performance gap.