```xml <result> <column_name>Hardware utilization (HFU)</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 utilization percentages is meaningless), product (not a ratio between states)</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. "Utilization" is a classic intensive measure—a level or percentage representing current state intensity at a point in time. The values [0.24, 0.93] are bounded percentages/fractions, not centered near 1.0 (ruling out ratio_multiplicative), and not unbounded magnitudes (ruling out real_additive). Summing utilization across entities is meaningless; averaging is the natural rollup. High null fraction (99.3%) suggests sparse attribute data typical of dimension tables. </reasoning> <table_type_conflict>false</table_type_conflict> </result> ```