```xml <result> <column_name>Training dataset size (datapoints)</column_name> <family>additive</family> <subtype>real_additive</subtype> <confidence>0.95</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</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 "Training dataset size (datapoints)" contains the token "size" and describes a count/quantity, strongly signaling real_additive. The data shows large unbounded magnitude (min ~320M, max ~147T), strictly positive values with no zeros or negatives, and center far from 1.0—all consistent with an extensive count measure. Sum is the natural aggregation for combining dataset sizes across entities. </reasoning> <table_type_conflict>false</table_type_conflict> </result> ```