anchor.diff: +<script type="text/javascript" src="https://www.gstatic.com/charts/loader.js"></script>
   <div class="jumbotron jumbotron_img_responsive" id="header">
     <h1 class="display-3">Stop Sign Detector</h1>
   </div>
  
positive.code:   <h2>📊 Current Stats ⏱️</h2>
  </div>
  <div class="row">
    <div class="col">
      <%= @stats.observation_period_count %> Total scans, <%= @stats.stop_sign_log_count %> total suspected cases
    </div>
    <div class="col">
      <%= (@stats.seconds_observed/60/60).to_i.delimited %>+ Hours collected, spanning <%= (@stats.total_study_time/60/60/24).to_i.delimited %> days
  
negative.code: </div>
  <div class="row">
    <div class="col">
      ≈<%= MachineLearner.first(vote_method: "presence").estimated_count.delimited %> total cars seen, ≈<%= MachineLearner.first(vote_method: "full_scene").estimated_count.delimited %> seen long enough to measure. An estimated ≈<%= ((@stats.total_study_time/@stats.seconds_observed)*MachineLearner.first(vote_method: "presence").estimated_count).to_i.delimited %> cars have passed the sign, with an average of ≈<%= (((@stats.total_study_time/@stats.seconds_observed)*MachineLearner.first(vote_method: "presence").estimated_count) / (@stats.total_study_time/60/60/24)).to_i.delimited %> per day.
    </div>
  </div>
  <div class="row">
  