code: def process_results(self, doc, results):
      gold = doc["final_decision"]
      ll_yes, ll_no, ll_maybe = results
      pred = np.argmax(results)
      return {
          "acc": ["yes", "no", "maybe"][pred] == gold,
      }
  
file_path: lm-evaluation-harness/lm_eval/tasks/pubmedqa.py
imports: import numpy
  from lm_eval.base import rf, Task
  from lm_eval.metrics import mean
label_desc: Use image node_id 10 for calling the Pubmed_QA obj's underlying member method code with example usage: obj.process_results(doc, results) and returns: dict