Abstract: Described herein is a machine-learning model that categorizes and classifies regulatory text and methods for operation thereof. The machine-learning model may receive raw data. The raw data may be data in a file that includes a list of text examples (e.g., leaf node citation texts). One or more datasets may be annotated. A training, validation, and test dataset may be generated. The machine-learning model is used to determine one or more predictions regarding the category and classification of input data. The training dataset is used to train the machine-learning model, the validation dataset is used to tune the hyper parameters of the model, and the test dataset is used to evaluate its performance. The prediction(s) are stored or sent to one or more downstream applications.

Abstract: A container or container blank (100) comprises a base portion (2) having a pair of opposed side wall portions (3B,5B) and an opposed front wall portion (4B) and rear wall portion (6B), each wall portion (3B,4B,5B,6B) being connected to the base portion (2) at a fold line (3,4,5,6). Each side wall portion (3B,5B) has inner and outer sections (3B,7;5B,7) separated by a fold land, the sections being adapted for folding about the fold land to assume a position overlying one another, the outer section (7) including locking means (7A,7B) engagable in the base portion (2) to secure said overlying position. The front and rear wall portions (4B,6B) each have a riser section and a lid section (11,10). The base at least has attached thereto a web of material (12) adapted to retain an article within a container formed from the blank (100).