## 4 Experimental and Computational Results  
### Intrinsic Magnetic Field Inspection  
The background noise of the magnetic field, an inevitable component of any precision measurement, was addressed through a designed suppression strategy. This noise, which could significantly distort the accuracy of magnetic field data, was partially suppressed by recording six reference signals over two consecutive days. These recordings were conducted at the same time as the sample measurements to ensure temporal consistency and account for any environmental (in vitro) fluctuations. The collected reference data were processed to calculate a mean noise value, effectively representing the system's baseline EMI. This mean value was subsequently subtracted from all the measurements, yielding data that were significantly more representative of the intrinsic magnetic properties of the samples. The interference was primarily attributed to external factors such as electrical connections and devices operating near the experimental setup. By implementing this noise suppression technique, the level of unwanted background interference was reduced, thereby increasing the reliability and reproducibility of the measurements. A specialized script was developed and executed within the MATLAB R2024b software environment to facilitate the interpretation and presentation of the corrected data. This script converted the refined numerical datasets into detailed 2D graphical maps, which provided an intuitive and visually comprehensible representation of the spatial distribution of the intrinsic magnetic field.  
Figures 8 and 9 present the intrinsic magnetic field of the samples in a graphical format, with the intensity represented by colour gradients on a logarithmical scale. For clarity, the intensity scale of the intrinsic magnetic field is standardized across each row of figures, and the maximum value is uniformly applied within each row. This standardization is essential for accurately analysing the distribution and shape of the magnetic field within the samples. The measured quantity corresponds to the normalized DC voltage output of  
Figure 7: Training and convergence progress of designed CNN: representation of network accuracy versus number of iterations (**top**) and loss parameter versus number of iterations (**bottom**).  
The data demonstrate the inhomogeneous nature of the sensed magnetic field. Scans conducted from different sides of the sample reveal the absence of axial or central symmetry. However, distinct material behaviour at various annealing temperatures is evident. A notable trend is the decrease in field intensity with rising annealing temperatures, punctuated by a sharp drop and subsequent spike around \(T=1000\)\({}^{\circ}\)C. This phenomenon is particularly striking and warrants further investigation. Additionally, the results indicate that the samples exhibit a dipole moment dependent on processing conditions. The dipole effect is especially pronounced near \(T=1000\)\({}^{\circ}\)C but diminishes rapidly beyond this temperature range. These observations provide critical insights into the interplay between annealing conditions and magnetic field characteristics, underscoring the importance of continued research in this area.  
Figure 9: Experimental results: intrinsic magnetic field of inspected samples for different annealing temperatures, L (left side): (**a**) \(T=100\)\({}^{\circ}\)C; (**b**) \(T=200\)\({}^{\circ}\)C; (**c**) \(T=300\)\({}^{\circ}\)C; (**d**) \(T=400\)\({}^{\circ}\)C; (**e**) \(T=500\)\({}^{\circ}\)C; (**f**) \(T=600\)\({}^{\circ}\)C; (**g**) \(T=700\)\({}^{\circ}\)C; (**h**) \(T=800\)\({}^{\circ}\)C; (**i**) \(T=900\)\({}^{\circ}\)C; (**j**) \(T=1000\)\({}^{\circ}\)C; (**k**) \(T=1100\)\({}^{\circ}\)C; (**l**) \(T=1200\)\({}^{\circ}\)C. The dashed lines indicate the location of the sample during the investigation.