Abstract: The present invention relates to compositions comprising constituents, derivatives or extracts of cannabis. The invention also relates to uses of such compositions and methods of manufacturing them.

Abstract: The present invention relates to methods for preparing compositions comprising a constituent, derivative or extract of cannabis. The invention also relates to the compositions and products incorporating them.

Abstract: The present invention relates to compositions comprising active agents formulated for both buccal and gastric delivery wherein the composition also comprises one or more constituent, derivative or extract of cannabis and a further physiologically active agent.

Abstract: The present invention relates to compositions comprising a constituent, derivative or extract of Cannabis in a water soluble matrix. The invention also relates to uses of such compositions and methods of manufacturing them.

Abstract: The present invention relates to compositions comprising one or more constituent, derivative or extract of cannabis formulated for gastric delivery and one or more flavour or sensate formulated for buccal delivery.

Abstract: The present invention relates to compositions comprising a constituent, derivative or extract of cannabis in solution or in a solubilised form. The invention also relates to products including such compositions and methods of manufacturing them.

Abstract: Methods, systems, and techniques for density ratio estimation of data that includes a covariate variable (W) and a treatment variable (T). The density ratio estimation may be performed using a transformer-based architecture, and the density ratio may be used to control confounding bias in the data. An electronic representation of the data is obtained. At first and second self-attention layers, respectively, covariate variable embeddings based on the data representing the covariate variable and treatment variable embeddings based on the data representing the treatment variable are determined. Cross-attention embeddings based on the covariate and treatment variable embeddings are then determined at a cross-attention layer. At a linear layer and based on the cross-attention embeddings, a density ratio is estimated. The self-attention layers, cross-attention layer, and linear layer are trained using a loss function that determines a loss between an output of the linear layer and the density ratio.

Abstract: A computer system and method for answering a natural language question is provided. The system comprises at least one processor and a memory storing instructions which when executed by the processor configure the processor to perform the method. The method comprises receiving a natural language question, generating a SQL query based on the natural language question, generating an explanation regarding a solution to the natural language question as answered by the SQL query, and presenting the solution and the explanation.