Fig. shows the expected error in the predicted partial pressure of the analyte by the CF-GS (eqn. 7) as a function of residence time k i r . When k i r = 0, a CF is absent. Including a CF therefore increases the performance of the CF-GS (over the range of k i r shown). For a short residence time, the CF converts only a small fraction of the interferent. Consequently, the variance in the partial pressure of the interferent in the gas propagates through the CF, and the GS is still exposed to gas with, albeit reduced, a highly variable partial pressure of interferent. This corrupts the response of the sensor and, since our modified inverse problem in eqn. 5 assumes the partial pressure of the interferent is fixed at its mean, the prediction of the partial pressure of the analyte. On the other hand, for long residence times, the CF converts a large fraction of the analyte. This effectively diminishes the analytical sensitivity / signal-to-noise ratio of the GS to the analyte. An intermediate residence time balances the corruption in the predicted partial pressure of the analyte by variance in (i) the partial pressure of the interferent and (ii) measurement noise. a emanates from both measurement noise and the variance in the partial pressure of the interferent, which contributes to the response. The variance in M|P 0 a is largest (see thick bands) in the absence of a CF (k i r = 0) because of the high variance in the interferent concentration exposed to the sensor. Without the CF, the interferent therefore maximally corrupts the calibration curve. Fig. illustrates a tradeoff involved in increasing the residence time r : (1, beneficial) more of the interferent is converted, and the variance in M|P 0 a diminishes to that caused only by measurement noise (2, harmful) more of the analyte is also converted, decreasing the calibration sensitivity (slope of the calibration curve, ∂ P 0