Decreased k parameter for finding a proper recovery value.
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			@ -16,7 +16,7 @@ df = pd.DataFrame(data)
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# Recovery (%) = R_max / (1 + exp(-k * (Grade - x0)))
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# Models increasing recovery efficiency with grade using an S-curve
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R_max = 100   # Maximum theoretical recovery (%)
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k = 10        # Steepness of the logistic curve
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k = 5        # Steepness of the logistic curve
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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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