You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT".
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.

For instance, if the model were given the claim "the COVID vaccine is safe for healthy adults", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults."]
}

Claim: Serological responses to bacterial virome define clinical outcomes of italian patients infected with sars-cov-2

Abstract:
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the pandemic respiratory infectious disease COVID-19.
However, clinical manifestations and outcomes differ significantly among COVID-19 patients, ranging from asymptomatic to extremely severe, and it remains unclear what drives these disparities.
Here, we studied 159 hospitalized Italian patients with pneumonia from the NIAID-NCI COVID-19 Consortium using a phage-display method to characterize circulating antibodies binding to 93,904 viral peptides encoded by 1,276 strains of human viruses.
SARS-CoV-2 infection was associated with a marked increase in individual’s immune memory antibody repertoires linked to trajectories of disease severity from the longitudinal analysis also including anti-spike protein antibodies.
By applying a machine-learning-based strategy, we developed a viral exposure signature predictive of COVID-19-related disease severity linked to patient survival.
These results provide a basis for understanding the roles of memory B-cell repertoires in COVID-19-related symptoms as well as a predictive tool for monitoring its clinical severity.
{"verdict": "CONTRADICT", "evidence": ["Here, we studied 159 hospitalized Italian patients with pneumonia from the NIAID-NCI COVID-19 Consortium using a phage-display method to characterize circulating antibodies binding to 93,904 viral peptides encoded by 1,276 strains of human viruses."]}