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@ -21,7 +21,7 @@ x_0 = 0.8 # Grade at which recovery rate reaches ~50% of R_max
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df["Recovery (%)"] = (R_max / (1 + np.exp(-k * (df["Weighted Grade (%)"] - x_0)))) / 100
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# === Processing Cost Estimation (Linear Regression Model) ===
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# === Processing Cost Estimation (Regression from Real Cost Model) ===
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# Processing Cost ($/t) = A + B * Grade
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# Reflects increasing cost with higher grade due to more intensive processing
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A = 12 # Fixed base processing cost ($/t)
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