You will be shown a claim about public health, 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". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: BCG vaccine can boost the immune system enough to prevent healthcare workers from catching coronavirus.

Abstract:
The pandemic of coronavirus disease 2019 (COVID-19) presents an unprecedented challenge to rapidly develop new diagnostic, preventive and therapeutic strategies.
Currently, thousands of new COVID-19 patients are quickly enrolled in clinical studies.
We aimed to investigate the characteristics of the COVID-19 studies registered in ClinicalTrials.gov and report the extent to which they have incorporated features that are desirable for generating high-quality evidence.
On April 28, 2020, a total of 945 studies on COVID-19 have been registered in ClinicalTrials.gov; 586 studies are interventional (62.0%), the most frequent allocation scheme is the parallel group assignment (437; 74.6%), they are open-label and the most common primary purpose is the research on treatment.
Too many of the ongoing interventional studies have a small expected sample size and may not generate credible evidence at completion.
This might lead to a delayed recognition of effective therapies that are urgently needed, and a waste of time and resources.
In the COVID-19 pandemic era, it is crucial that the adoption of new diagnostic, preventive and therapeutic strategies is based upon evidence coming from well-designed, adequately powered and carefully conducted clinical trials.
{"verdict": "NEI", "evidence": []}