Large language models (LLMs) as agents for augmented democracy.

We explore an augmented democracy system built on off-the-shelf large language models (LLMs) fine-tuned to augment data on citizens' preferences elicited over policies extracted from the government programmes of the two main candidates of Brazil's 2022 presidential election. We use a train-test cross-validation set-up to estimate the accuracy with which the LLMs predict both: a subject's individual political choices and the aggregate preferences of the full sample of participants. At the individual level, we find that LLMs predict out of sample preferences more accurately than a 'bundle rule', which would assume that citizens always vote for the proposals of the candidate aligned with their self-reported political orientation.

Understanding political divisiveness using online participation data from the 2022 French and Brazilian presidential elections.

Digital technologies can augment civic participation by facilitating the expression of detailed political preferences. Yet, digital participation efforts often rely on methods optimized for elections involving a few candidates. Here we present data collected in an online experiment where participants built personalized government programmes by combining policies proposed by the candidates of the 2022 French and Brazilian presidential elections.

[Surgical treatment of chronic pericardial effusions. Personal experience].

The authors report their experience about 15 patients surgically treated for chronic large pericardial effusion; in 12 cases the etiology was malignant neoplasm, while in the other 3 cases was inflammatory disease. In 4 patients a simple subxiphoid pericardial drainage was carried out, while in the other cases a pericardial window was performed. These cases were managed using an anterior left thoracotomy in 8 patients and a videothoracoscopy in 3.

Role of videoendoscopy in pulmonary surgery: present experience.

Videothoracoscopic techniques were utilized in managing 88 consecutive patients. The series was composed of 36 patients with pneumothorax, 44 cases of single and 9 of multiple pulmonary nodules and 1 patient with diffuse lung disease. In 14 cases (15.