GoldSpot Discoveries Corp. and Critical Elements Lithium Corporation announced the results of a propertywide comprehensive data review, compilation, and target generation on Critical Element's New Block 16 and 7 claims within the prolific Nemiscau greenstone belt in James Bay, Québec. This study hinged on digital extraction from an exhaustive collection of compiled data, including assessment files, government data and academic studies. This dataset provided outcrop/sample description, bedrock geology, geochemical analyses, and geophysical surveys. Original data cleaned and combined to create a comprehensive data set for geological interpretation and machine learning processes. Geological Interpretation: The compilation of discrete outcrop observations allowed a reliable update to existing geologic maps, resulting in a refined pegmatite map. A total of 42 pegmatite bodies were added to the current geological map, highlighting previously unknown potential for economic lithiumtantalum mineralization. An uptodate structural interpretation was created based on a highresolution aeromagnetic survey commissioned by Critical Elements. This survey revealed structurally complex patterns, including largescale folds and major ENEtrending ductile fault zones. Processes: The AI data analysis trains machine learning algorithms to predict the presence of lithiumtantalum (model 1), coppernickel (model 2), and gold (model 3), using all variables (features), both numeric and interpreted on a 10 x 10 m grid cell datacube. Once the model performs to a satisfactory level, results produced include: 1) a series of zones with relatively high probability of containing lithium and tantalum (model 1; same process for models 2 and 3); o 2) a ranking of feature importance for each input feature. Performance: The best prediction model for the lithiumtantalum model was obtained using a Random Forest classifier for which performance metrics were above 80% precision. The updated geology and structural interpretation were the dominant contributors to the targeting model. These targets highlight the outer zones of felsic batholiths as the most prospective areas of the claims of scope, including ENE trends at both northern and southern margins of the pertained claims. In addition to lithiumtantalum targets, a total of 5 coppernickel and 7 gold targets were identified. These targets commonly occur in similar geological settings: areas of intense structural complexity where a diversity of rock units occurs, including mafic units, felsic intrusions and paragneiss. In addition to the targeting, GoldSpot provided a map of probable outcrop zones to support future field programs. More than 75% of the existing outcrops were found by the machine learning model, highlighting the predictive accuracy of this approach. The machine learning assisted outcrop detection allows for time and costefficient field exploration. The area of interest occurs in the southeastern part of the Nemiscau Subprovince. The northern Nemiscau Subprovince is marked by the volcanosedimentary rocks of the Lac des Montagnes Group which consists of mafic to felsic volcanic units and iron formations. These Archean volcanosedimentary packages are affected by major NEtrending ductile shear zones (Pedreira et al., 2020) during the Kenoran orogeny (2720 2680 Ma). Local geology exposes metamorphosed sediments units (i.e., paragneiss from the Rupert Complex and Voirdye Formation), syntectonic intrusives (that is De la Hutte Complex and The Canard Suite) and posttectonic pegmatites (i.e., Mezière Suite and Spodumène Suite).