<result> <column_name>age</column_name> <family>additive</family> <subtype>intensive_additive</subtype> <confidence>0.82</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 ages across entities is meaningless), 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> The table is a DIMENSION with no sequence axis, so multiplicative is implausible and no reconstruction signals are available. Age is an absolute level or intensity attribute: values range from 18 to 65, centered near 34 (far from 0 and 1), with no ratio-style naming. Summing ages across merged entities has no meaning, while the mean is the natural rollup, so it is intensive_additive. The positive log_symmetry_gain only reflects right skew of a bounded positive variable and is not evidence of a multiplicative measure. Age is arguably a descriptive dimension attribute rather than a true measure, which keeps confidence below the highest tier. </reasoning> <table_type_conflict>false</table_type_conflict> </result>