```xml <result> <column_name>Training power draw (W)</column_name> <family>additive</family> <subtype>intensive_additive</subtype> <confidence>0.85</confidence> <requires_user_confirmation>false</requires_user_confirmation> <sum_meaningful>false</sum_meaningful> <signed>false</signed> <reducers> <primary_reducer>mean</primary_reducer> <valid_reducers>mean, min, max, median, distribution</valid_reducers> <excluded_reducers>sum (summing power draw across entities is meaningless - power is an intensive physical quantity), product (not a ratio)</excluded_reducers> <average_semantics>arithmetic_mean</average_semantics> </reducers> <inner_outer_measure> <inner_measure_reducer>min</inner_measure_reducer> <outer_measure_reducer>max</outer_measure_reducer> </inner_outer_measure> <multiplicative_partner_derivable>false</multiplicative_partner_derivable> <reasoning> Table type is DIMENSION with no sequence axis, making multiplicative highly implausible. The column name "Training power draw (W)" clearly indicates an instantaneous physical intensity (power in watts), which is a classic intensive quantity. Power draw is a level measurement at a point in time - summing power values across different entities is physically meaningless (you cannot add "100W + 200W = 300W of total power" for separate systems). The wide magnitude range (75W to 109M W) and strictly positive values are consistent with absolute power measurements across diverse systems. Intensive_additive is the correct classification, with mean as the natural aggregation. </reasoning> <table_type_conflict>false</table_type_conflict> </result> ```