```xml <result> <column_name>f_boxer_lost</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 type is DIMENSION with no sequence axis, making multiplicative highly implausible (gate prior). Column name "f_boxer_lost" suggests a count or frequency measure (the "f_" prefix often denotes frequency/count). The data is strictly non-negative with zeros excluded from the sample but min=0.0 in statistics, ranging from 0.0 to ~3.77, which is consistent with a count or accumulated loss metric. No naming tokens suggest ratio/rate/percentage, and values are not centered near 1.0. This is clearly an extensive quantity (losses accumulated) that sums meaningfully across entities. </reasoning> <table_type_conflict>false</table_type_conflict> </result> ```