```xml <result> <column_name>billable_input_tokens</column_name> <family>additive</family> <subtype>real_additive</subtype> <confidence>0.85</confidence> <requires_user_confirmation>false</requires_user_confirmation> <sum_meaningful>true</sum_meaningful> <signed>false</signed> <reducers> <primary_reducer>sum</primary_reducer> <valid_reducers>sum, min, max, mean, median, count, distribution</valid_reducers> <excluded_reducers>product (not a ratio), geomean (not a ratio)</excluded_reducers> <average_semantics>arithmetic_mean</average_semantics> </reducers> <inner_outer_measure> <inner_measure_reducer>sum</inner_measure_reducer> <outer_measure_reducer>sum</outer_measure_reducer> </inner_outer_measure> <multiplicative_partner_derivable>false</multiplicative_partner_derivable> <reasoning> Table is DIMENSION with no sequence axis, making multiplicative highly implausible per gate prior. Column name "billable_input_tokens" contains strong real_additive signal: "tokens" is a countable quantity, and "billable" suggests an accumulated usage metric. The name pattern matches count/quantity semantics. No zeros detected (has_zeros=false) and no negatives (has_negatives=false) consistent with a non-negative count. Despite object dtype and null statistics (likely a data quality issue), the semantic naming is decisive for real_additive classification. </reasoning> <table_type_conflict>false</table_type_conflict> </result> ```