1. https://ieeexplore-ieee-org.prox.lib.ncsu.edu/stamp/stamp.jsp?tp=&arnumber=8372026
   Comparing Manual Scores to Resumes Against Auto Scores.
   Evaluation is by precision and the precision is calculated by using the percentage delta between predicted and actual.

2. https://ieeexplore-ieee-org.prox.lib.ncsu.edu/stamp/stamp.jsp?tp=&arnumber=7429390 The evaluation is made during runtime with Adaptative Learning. The resumes matched can be selected as relevant or irrelevant very similar to Zhe's fast read method.

3. https://ieeexplore-ieee-org.prox.lib.ncsu.edu/stamp/stamp.jsp?tp=&arnumber=8372089 The evaluation metric is the recall. They have the resumes pre-selected for certain jobs and they are worried whether they recommend the good resumes to the job and not so much worried if they have false positives.

4. https://ieeexplore-ieee-org.prox.lib.ncsu.edu/stamp/stamp.jsp?tp=&arnumber=8396176 They are predicting three things for the future based on resume. The scale of the company the resume will work on, the salary and position. They have the ground truth labels before and the options. The results have very low precision. And could be something to work on with room for improvement.

| | add: Num1
| | col: 3
| | hi: -inf
| | lo: inf
| | m2: 0
| | mu: 0
| | n: 0
| | oid: 3
| | sd: 0
| | txt: <humid

hi, lo, m2, mu, n and sd are incorrect