You will be shown a scientific claim, 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 "smoking causes cancer", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["The results of our meta-analysis provide overwhelming support that cigarette smoking is a risk cause for lung cancer."]
}

Your response should not include any text other than the json.

Claim: Students who perform poorly in the early years of medical school are at increased risk for professional misconduct later in their careers.

Abstract:
OBJECTIVE To determine whether there are risk factors in a doctor's time at medical school that are associated with subsequent professional misconduct.
DESIGN Matched case-control study.
Setting Records from medical schools and the General Medical Council (GMC).
PARTICIPANTS 59 doctors who had graduated from any one of eight medical schools in the United Kingdom in 1958-97 and had a proved finding of serious professional misconduct in GMC proceedings in 1999-2004 (cases); 236 controls (four for each case) were selected by systematic sampling from matching graduation cohorts.
Case-control status was revealed by the GMC after completion of data entry.
MAIN OUTCOME MEASURE Odds ratios for being a "case," with multivariable conditional logistic regression of potential risk factors including pre-admission characteristics and progress during the course.
These data were obtained from anonymised copies of the students' progress files held by their original medical schools.
RESULTS Univariate conditional logistic regression analysis found that cases were more likely to be men, to be of lower estimated social class, and to have had academic difficulties during their medical course, especially in the early years.
Multivariable analysis showed that male sex (odds ratio 9.80, 95% confidence interval 2.43 to 39.44, P=0.001), lower social class (4.28, 1.52 to 12.09, P=0.006), and failure of early or preclinical examinations (5.47, 2.17 to 13.79, P<0.001) were independently associated with being a case.
CONCLUSIONS This small study suggests that male sex, a lower socioeconomic background, and early academic difficulties at medical school could be risk factors for subsequent professional misconduct.
The findings are preliminary and should be interpreted with caution.
Most doctors with risk factors will not come before the GMC's disciplinary panels.
{"verdict": "SUPPORT", "evidence": ["RESULTS Univariate conditional logistic regression analysis found that cases were more likely to be men, to be of lower estimated social class, and to have had academic difficulties during their medical course, especially in the early years.", "Multivariable analysis showed that male sex (odds ratio 9.80, 95% confidence interval 2.43 to 39.44, P=0.001), lower social class (4.28, 1.52 to 12.09, P=0.006), and failure of early or preclinical examinations (5.47, 2.17 to 13.79, P<0.001) were independently associated with being a case.", "CONCLUSIONS This small study suggests that male sex, a lower socioeconomic background, and early academic difficulties at medical school could be risk factors for subsequent professional misconduct."]}