Term #2,403
Classification boundaries
Claim Term
Classification boundaries
Origin matter
A method for screening manuscripts
Reference Case 1
BRT_PAT-2-PROV
Date Added
1/7/26
Created
1/7/26, 7:33 PM
Modified
8/18/26, 4:56 PM
Full Desc
“Classification boundaries” refers to one or more decision thresholds, rules, learned parameters, or dividing functions used by a computational model to distinguish among different categories, labels, or outcome classes. Classification boundaries may be explicit (e.g., rule-based or threshold-based) or implicit (e.g., learned by a machine-learning model), and may operate in one or more dimensions of a feature space, embedding space, or probability distribution. In certain embodiments, classification boundaries are used by an artificial-intelligence system to determine how a manuscript or portion of a manuscript should be categorized relative to one or more screening or editorial outcomes, such as 'reject' or 'not reject'.
Applications using this term
| Matter | Usage | Notes | Actions |
|---|---|---|---|
| BRT-PAT-2-PROV | Defined | — | App terms |