{"pre_text": ["interest expense 2013 interest expense increased in 2014 versus 2013 due to an increased weighted- average debt level of $ 10.8 billion in 2014 from $ 9.6 billion in 2013 , which more than offset the impact of the lower effective interest rate of 5.3% ( 5.3 % ) in 2014 versus 5.7% ( 5.7 % ) in 2013 .", "interest expense decreased in 2013 versus 2012 due to a lower effective interest rate of 5.7% ( 5.7 % ) in 2013 versus 6.0% ( 6.0 % ) in 2012 .", "the increase in the weighted-average debt level to $ 9.6 billion in 2013 from $ 9.1 billion in 2012 partially offset the impact of the lower effective interest rate .", "income taxes 2013 higher pre-tax income increased income taxes in 2014 compared to 2013 .", "our effective tax rate for 2014 was 37.9% ( 37.9 % ) compared to 37.7% ( 37.7 % ) in 2013 .", "higher pre-tax income increased income taxes in 2013 compared to 2012 .", "our effective tax rate for 2013 was 37.7% ( 37.7 % ) compared to 37.6% ( 37.6 % ) in 2012 .", "other operating/performance and financial statistics we report a number of key performance measures weekly to the association of american railroads ( aar ) .", "we provide this data on our website at www.up.com/investor/aar-stb_reports/index.htm .", "operating/performance statistics railroad performance measures are included in the table below : 2014 2013 2012 % (  % ) change 2014 v 2013 % (  % ) change 2013 v 2012 ."], "post_text": ["average train speed 2013 average train speed is calculated by dividing train miles by hours operated on our main lines between terminals .", "average train speed , as reported to the association of american railroads , decreased 8% ( 8 % ) in 2014 versus 2013 .", "the decline was driven by a 7% ( 7 % ) volume increase , a major infrastructure project in fort worth , texas and inclement weather , including flooding in the midwest in the second quarter and severe weather conditions in the first quarter that impacted all major u.s .", "and canadian railroads .", "average train speed decreased 2% ( 2 % ) in 2013 versus 2012 .", "the decline was driven by severe weather conditions and shifts of traffic to sections of our network with higher utilization .", "average terminal dwell time 2013 average terminal dwell time is the average time that a rail car spends at our terminals .", "lower average terminal dwell time improves asset utilization and service .", "average terminal dwell time increased 12% ( 12 % ) in 2014 compared to 2013 , caused by higher volumes and inclement weather .", "average terminal dwell time increased 3% ( 3 % ) in 2013 compared to 2012 , primarily due to growth of manifest traffic which requires more time in terminals for switching cars and building trains .", "gross and revenue ton-miles 2013 gross ton-miles are calculated by multiplying the weight of loaded and empty freight cars by the number of miles hauled .", "revenue ton-miles are calculated by multiplying the weight of freight by the number of tariff miles .", "gross ton-miles , revenue ton-miles and carloadings all increased 7% ( 7 % ) in 2014 compared to 2013 .", "gross ton-miles and revenue ton-miles declined 1% ( 1 % ) in 2013 compared to 2012 and carloads remained relatively flat driven by declines in coal and agricultural products offset by growth in chemical , autos and industrial products .", "changes in commodity mix drove the year-over-year variances between gross ton- miles , revenue ton-miles and carloads. ."], "table": [["", "2014", "2013", "2012", "% (  % ) change 2014 v 2013", "% (  % ) change2013 v 2012"], ["average train speed ( miles per hour )", "24.0", "26.0", "26.5", "( 8 ) % (  % )", "( 2 ) % (  % )"], ["average terminal dwell time ( hours )", "30.3", "27.1", "26.2", "12 % (  % )", "3 % (  % )"], ["gross ton-miles ( billions )", "1014.9", "949.1", "959.3", "7 % (  % )", "( 1 ) % (  % )"], ["revenue ton-miles ( billions )", "549.6", "514.3", "521.1", "7 % (  % )", "( 1 ) % (  % )"], ["operating ratio", "63.5", "66.1", "67.8", "( 2.6 ) pts", "( 1.7 ) pts"], ["employees ( average )", "47201", "46445", "45928", "2 % (  % )", "1 % (  % )"]], "table_ori": [["", "<i>2014</i>", "<i>2013</i>", "<i>2012</i>", "<i>% Change</i> <i>2014 v 2013</i>", "<i>% Change</i><i>2013 v 2012</i>"], ["Average train speed (miles per hour)", "24.0", "26.0", "26.5", "(8)%", "(2)%"], ["Average terminal dwell time (hours)", "30.3", "27.1", "26.2", "12 %", "3 %"], ["Gross ton-miles (billions)", "1,014.9", "949.1", "959.3", "7 %", "(1)%"], ["Revenue ton-miles (billions)", "549.6", "514.3", "521.1", "7 %", "(1)%"], ["Operating ratio", "63.5", "66.1", "67.8", "(2.6)pts", "(1.7)pts"], ["Employees (average)", "47,201", "46,445", "45,928", "2 %", "1 %"]]}

Question: holding weighted- average debt level as the same as 2013what would the interest expense be in 2014 in billions?
Evidence:
text_0: interest expense 2013 interest expense increased in 2014 versus 2013 due to an increased weighted- average debt level of $ 10.8 billion in 2014 from $ 9.6 billion in 2013 , which more than offset the impact of the lower effective interest rate of 5.3% ( 5.3 % ) in 2014 versus 5.7% ( 5.7 % ) in 2013 .
Program: multiply(9.6, 5.3%)
Answer:
str_answer: .508
exe_answer: 0.5088