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c∈{V,H}c\in\{V,H\}

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Define the channel-attributable transfer rate for exposure class c∈\in\{V,H\} as TcT_c=Iˉc−I01−I0\frac{\bar I_c-I_0}{1-I_0} . This is a direct borrowing from the attributable-risk fraction used in outbreak epidemiology, where it measures what share of disease in an exposed group would disappear if the exposure were removed; here it measures what share of a model’s trait incidence would disappear if its exposure to the source artifact were removed, holding everything else about the model constant. TcT_c=0 means the exposed class shows the trait no more often than baseline: no signal. TcT_c=1 means every trait-negative case in the exposed class would have been positive under full exposure: the strongest…

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cc

Symbol c

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VV

Symbol V

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HH

Symbol H

H is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

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c∈{V,H}c\in\{V,H\}

Equation 21 · Evolutionary AI

A Chatbot Confessed to Being Built by a Company That Never Trained It

This mathematical expression combines the displayed quantities; its precise role follows from the surrounding article text.

Define the channel-attributable transfer rate for exposure class c∈\in\{V,H\} as TcT_c=Iˉc−I01−I0\frac{\bar I_c-I_0}{1-I_0} . This is a direct borrowing from the attributable-risk fraction used in outbreak epidemiology, where it measures what share of disease in an exposed group would disappear if the exposure were removed; here it measures what share of a model’s trait incidence would disappear if its exposure to the source artifact were removed, holding everything else about the model constant. TcT_c=0 means the exposed class shows the trait no more often than baseline: no signal. TcT_c=1 means every trait-negative case in the exposed class would have been positive under full exposure: the strongest…

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