## 2 Materials and Methods
### Wildlife Image CT Data  
GMERC Ltd. (Busongola, Tanzania) researchers previously obtained the wildlife CT data at the Issa research station between 2016-2020 from Bushnell fixed-local-length CTs. We initially selected 15 species, 4 of which were removed during the model training, resulting in 11 species for testing. We selected the following species _C. crocuta, Philantomba monticola, Potamocheurs larvaatus, Tragelaphus sylvaticus, Genetta tigrina, Pan troglodytes schuevitfurthii, Sylvicapra grinminu, Hytsrix cristata, Panthera pardus, Cercopithecus ascanius_, and _Papio cynocephalus_. Following this, we selected the factors measured depending on their frequency within the species-specific CT footage and based on previous findings [16; 17; 19; 20; 21; 22; 23]. The chosen factors include each species' height (shoulder height), species differences (species-specific visual traits), time-of-day (for cathemeral species), the distance of the animal to the CT, occlusion of an animal from the CT, and animal orientation relative to the CT, as explained below. We identified each species' shoulder heights, previously assessed using the perpendicular distance between the base of the heel and the shoulder blade as according to Kingdon [28] and categorised these measurements into three categories \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Variable** & **Effect** & **Classification Labels** & **Variable Type** \\ \hline Outcome Variable & & & \\ Detection 1 & Target & False-negative = 1/True-positive = 2 & Binary \\ Correct Classification 1 & Target & False-negative = 1/True-positive = 2 & Binary \\ Predictor Variables & & & \\ Occlusion 1 & Fixed & 0–33\% = 1, 34–67\% = 2, and 68–100\% = 3 & Nominal \\ Distance 1 & Fixed & \textless{}5, 5, 10, 15, 20, 25, and 30 m/0–4.9 = 1, & Nominal \\  & & 5-9.9 = 2, and \(\geq\)10 = 3 & Nominal \\ Orientation Towards the CT 1 & Fixed & Yes = 1/No = 2 & Binary \\ Analyst Performance 1 & Fixed & Analyst 1, 2, 3 & Nominal \\ Vegetation Type 2 & Fixed & Miombo Woodland = 1/Rivering Forest = 2 & Binary \\ Colour 2 & Fixed & Blue = 1/Green = 2 & Binary \\ Height 2 & Fixed & Participant height in metres & Continuous \\ Species 3 & Fixed & Species scientific name identified & Nominal \\  & & numerically (1–11) & Nominal \\ Size Classes 3 & Fixed & Small = 1, Medium = 2, and Large = 3 & Nominal \\ Hierarchical Variables & & & \\ Experiment Number 2 & Random & Identification number of the experiment & Nominal \\ Tree Tag Number 3 & Random & Identification number of the tree tag & Nominal \\ \hline \hline \end{tabular}  
Notes: 1 both wildlife and human factors; 2 human factors; 3 wildlife factors.  
\end{table} 
Table 1: The tested variables within both human and wildlife experiments, showing each variable name, their type of effect on the experimental outcome, their associated classification (dummy data) label, and each variable type. (small 0-4 m, medium 4.1-7 m, and large 7.1-10 m). We used the factor species to represent species ID and general species-specific characteristics, including colour, body shape, and antlers/horns. Proceeding this, we identified each species' circadian cycles, including cathemeral (daylight/dusk), nocturnal (dusk), and diurnal (daylight) [29; 30; 31; 32; 33; 34; 35; 36; 37]. This enabled us to ensure adequate footage was obtained of cathemeral species at both daylight (7:00-18:00) and dusk (18:01-5:00) for measuring the time-of-day factor. We measured the distance factor in classes (0-5, 5-10, and >10 m) at five different tree tag locations (4800, 3219, 4817, 4816, and 4815), selected based on the level of species abundant at each site. Once we had set the distance classes, we recorded the distance and position (relative to the CT) of the most predominant trees within each class in a forward-facing direction to use as reference points for measuring species distances within pre-captured CT images. GMERC Ltd. researchers captured all CT footage with a fixed focal length lens, using consistent video resolution (1900 \(\times\) 1080).