[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:n_genotypes = 3\nn_measurements = 10  # it is trivial to make 10 measurements on the plate reader\nplate1_control = np.random.normal(10, 1, size=(n_measurements, 1))\nplate1_empty = np.random.normal(1, 1, size=(n_measurements, 1))\nplate1_sample_mus = np.random.uniform(low=0.1, high=200, size=n_genotypes)\nplate1_sample_sds = np.random.exponential(scale=5, size=n_genotypes)\nplate1_sample_data = np.random.normal(loc=plate1_sample_mus, scale=plate1_sample_sds, size=(n_measurements, n_genotypes))\nplate2_control = np.random.normal(13, 1, size=(n_measurements, 1))\nplate2_empty = np.random.normal(3, 1, size=(n_measurements, 1))\nplate2_sample_mus = plate1_sample_mus + 3  # plate2 is a systematic shift from plate 1\nplate2_sample_sds = plate1_sample_sds      # but has the same variance\nplate2_sample_data = np.random.normal(loc=plate2_sample_mus, scale=plate2_sample_sds, size=(3, n_genotypes))\nplate3_control = np.random.normal(13, 2, size=(n_measurements, 1))\nplate3_empty = np.random.normal(3, 2, size=(n_measurements, 1))\nplate3_sample_mus = plate1_sample_mus + 3                            # plate2 is a systematic shift from plate 1\nplate3_sample_sds = np.random.exponential(scale=3, size=n_genotypes) # and has greater potential variance\nplate3_sample_data = np.random.normal(loc=plate3_sample_mus, scale=plate3_sample_sds, size=(3, n_genotypes))'}, {'role': 'assistant', 'content': "['load_data']"}]