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The mightiest machines produced by human ingenuity are indeed useless unless guided and serviced by the intelligence and skill of man. We are, of course, very proud of our mechanical equipment, but we are prouder still of the men who keep it running. The New Haven Railroad is more than just ties, rails, and rolling stock. It is primarily people. People whose skill, devotion, courage, and strict adherence to the finest railroad practices have made possible its record of safety, efficiency, and progress. Right, Mr. Palmer. Now let's have motion pictures. Take us behind the scenes of a great railroad at work. We'll see two general phases, railroad operation and railroad maintenance. Trains are of two kinds, passenger and freight. Let's begin with the passenger, the locomotive backing into the yards to pick up the cars of the Yankee Clipper. The cars, meanwhile, have been made ready for the passengers, and having them clean and sanitary is rule A in the art of railroading. Repair shops. Here passenger coaches' dining cars and grill cars are brought to be repaired or rebuilt. They're put through the latest processes of cleaning and sanitation. There's an imposing background of work behind the picture of a smart modern car and a passenger train. The ceiling of car windows. And here we find a device of technical science to enable you to see better as you gaze at the scenery. Each streamlined window consists of two panes of glass held apart by rubber spacers. These rubber spacers seal the inner surfaces of the glass against the outside air. Between the panes, dry nitrogen is forced to keep them from being fogged by condensing moisture. Into the yards backs the locomotive to pick up the cars. Meanwhile, at the commissary, supplies of food and drink for the dining car are being allotted and checked. Have some chicken fritter here tonight. Yeah, that's very nice. The amount of groceries they can stow into the small pantry space that car dimensions permit would make a housewife think that it's all magic. But then, as the ponderous locomotive backs gently and is coupled to the cars, we may reflect that there is a lot of magic in a railroad. The clipper pulls out of the yards on its way to the station, everything timed to the second. On this railroad, hundreds of passenger trains are made up every day, in addition to hundreds of freight trains. They operate through southern New England day and night with the magic of timing. Strange geometries of tracks in the yards and the number of switches there calls for death and intricate manipulation. Into the station, the train can be controlled, air brake, by the rear trainman as well as by the engineer in front, a large factor of safety. South Station in Boston, the old familiar scene and never without a thrill. Passenger is going to a train. This is our little girl. She's going all the way to the yard. You take good care of her, don't you? You really will, ma'am. Step right in. Bye, darling. Hey, wait a minute. What? What? What? A woman in Boston buying a bicycle for her nephew in New York, and he'll get it the next day. This takes us to the subject of freight trains. Shipments of freight are in two classes, carloads and less than carload lots. Delivered to the freight depot and recorded with a waybill, the boy's bicycle is stowed safely and securely for the trip. There's an art in stowing all sorts of freight securely in a car and also in switching the cars through the yard. The powerful diesel switcher is the last word in this type of modern mechanism, one of the busiest of workers in the realm of railroading, practically a 24-hour a day worker. A new coordination of rail and highway transportation is seen as they load a trailer onto a flat car. The trailer has picked up packages from all over Boston to be distributed in New York. Ordinarily, the tractor pulling the trailer would have made the trip to New York by highway, but now the trailer is securely fastened on the flat car and then carried to the metropolis. This avoids a truck trip to New York, a large saving of gasoline and of rubber tires. Mighty important in these days of wartime shortages with rubber tires rationed. The steam locomotive is coupled to the cars and the theme is industrial products of New England on their way. They represent the work and skill of New England factories. Transporting them is an equal task of work and skill. The mighty system of operations embodied in the speeding freight train and the rhythm of the rails seems to save New England at work, New England on the move. A signal tower which trains to and from New York will pass, one of many sentinels of safety, vigilant alertness 24 hours a day. When a train passes, the signal man flashes the report to division headquarters. Gotten less 177 by a 215, engine 1404 with 13 cars. Line up on track one for the purpose. The freight angle intervenes. For railroads, two categories, passenger and freight, are another form of life's two divisions, people and things. South America is the destination of this large and intricate machine. Carefully created, it will go by ship, but first it must be taken by rail down New England to the harbor. An export angle of freight service. Industrial New England is of historic importance in the foreign trade of this nation. Passenger service takes plenty of account of passengers' appetites. The grill car is for the less formal meal than the diner provides. Thank you. Do you suppose I can have that roast beef rare? Very much. All right, and I'd like rare roast beef with mashed potatoes and peas. Like something to drink? Yes, tea with lemon. Tea with lemon, thank you. The dining car is a place of leisurely luxury, regaining yourself while the passing scenery provides entertainment. One borer, Boston Scribe. And the scribe is very nice today. One French fired potato, one lettuce and a metre salad, one coffee, one hour for five. How's your Boston Scribe, French fried potatoes? Coming up. Get up on the Boston Scribe. You can walk on the Scribe. Thank you, sir. Grab a soup, please. This classification yard shows us an ingenious angle of freight transportation. It has a sort of hill, which they call the hump. This hill is a key factor in what we'll see, the classification of freight cars. They are oiled while on the move, on their way up the hump. They go on to the top of the slope. The purpose of all this is to classify incoming trains so they can be reassembled as other trains, each to go to a different destination. A yard master directs the switching. The car is to be switched to various tracks. On your second seat, 22 to 24, 43 to 33, 48 to 13. At the top of the hump, cars are uncoupled and they roll down by gravity. Some cars would get up to much speed if it weren't for the retarder, a device for checking their seat. One of the 26 cars... In the retarding tower, the speed is governed, electrically controlled. Switches direct the cars to the right tracks, where they join other cars to make new trains for other destinations. We see the crate of machinery for South America going over the hump. The train in which this car arrived consists of cars bound for different destinations. In the classification yard, it will join a train going to the harbor. Less than carload lots are reclassified as this LCL transfer. Just as whole trains must be rearranged with reference to the destinations of the cars, so must individual consignments of merchandise in a car be rearranged with reference to their destinations. And this is done here. The car is unloaded and the merchandise is reassembled in other cars. These cars are then attached to trains bound for many, many places. The engine house, where running repairs are made. We see another phase of railroading, maintenance of equipment. There are light repairs made at many points on the railroad. And there are heavy repairs, which are made in a great locomotive shop. Here's a ponderous fantasy of fire and steel, the mighty forge of a modern Vulcan. All locomotives are overhauled periodically. Each one after going from 120,000 to 400,000 miles is sent to the shop for a complete overhauling. The slip track is an oil track where overhauled locomotives get final tests. They can be driven many miles at all speeds forward and backward on a track that simulates conditions of speed. A monster locomotive thoroughly overhauled is a symbol of that factor so vital in all mechanics, all industry, maintenance. A mechanized army, for example, is as good as its maintenance, and so is a railroad. A locomotive must be serviced, and that occurs at many places along the line. It requires, for example, sand, to give the big drive wheels traction when the rails are wet and slippery. And coal, to be blown automatically into the firebox. The fireman just operates a lever. The coal pile is a mountain. Countless tons of the black fuel stored against any emergency, anything that might cause a shortage. The coal pile tells us that a railroad is not only a mover of things, it is also a buyer of things. This we see vividly at one of the warehouses, docked with shovels, brooms, locomotive and car replacement parts, tools for track, shop and building maintenance, signal equipment, and countless other miscellaneous items a railroad needs. Ties go with rails as ham with eggs. As in the case of coal, the stocks of railroad ties are immense, a matter of acres. It takes more than 3,000 ties to make just one mile of standard railroad track. Lumber to hold up steel. And oil for fuel for every sort of lubrication and for paint. Salvage is a large activity. Everything possible is saved and put away for future use. Railroad economy. Laboratory tests for all vital materials purchased by the railroad. Metals, for example, are subjected to exacting tests. In the chemical laboratories, the magic of modern alchemy is applied to the checking of the materials in the interest of safety, efficiency, and economy. And there's research here to find new things, new combinations, new ways of applying chemical science to railroading. The micro-metallograph camera analyzes many materials for railroading with ultra-modern science. The vast amount of technology research, experimentation is embodied, for example, in these exceedingly modern diesel road locomotives, which are capable of being used with equal effectiveness in either pass or pass.", "segments": [{"id": 0, "seek": 0, "start": 0.0, "end": 7.92, "text": " THE T", "tokens": [50363, 3336, 309, 50617], "temperature": 1.0, "avg_logprob": -4.468387179904514, "compression_ratio": 0.7391304347826086, "no_speech_prob": 0.45809274911880493, "words": [{"word": " THE", "start": 0.0, "end": 3.96, "probability": 0.001418778207153082}, {"word": " T", "start": 3.96, "end": 7.92, "probability": 0.013114065863192081}]}, {"id": 1, "seek": 0, "start": 7.92, "end": 7.92, "text": "", "tokens": [], "temperature": 1.0, "avg_logprob": -4.468387179904514, "compression_ratio": 0.7391304347826086, "no_speech_prob": 0.45809274911880493, "words": []}, {"id": 2, "seek": 0, "start": 7.92, "end": 7.92, "text": "", "tokens": [], "temperature": 1.0, "avg_logprob": -4.468387179904514, 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Now let's have motion pictures. Take us behind the scenes of a great railroad at work. 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Switches direct the cars to the right tracks, where they join other cars to make new trains for other destinations.", "tokens": [50613, 554, 262, 1005, 13493, 10580, 11, 262, 2866, 318, 21825, 11, 30880, 1146, 6856, 13, 2451, 9249, 1277, 262, 5006, 284, 262, 826, 8339, 11, 810, 484, 4654, 584, 5006, 284, 787, 649, 13404, 329, 584, 23982, 13, 51163], "temperature": 0.0, "avg_logprob": -0.2355200958251953, "compression_ratio": 1.4217687074829932, "no_speech_prob": 0.008501697331666946, "words": [{"word": " In", "start": 1042.6, "end": 1042.6, "probability": 0.26517823338508606}, {"word": " the", "start": 1042.6, "end": 1042.7, "probability": 0.9893145561218262}, {"word": " retarding", "start": 1042.7, "end": 1043.1, "probability": 0.959124356508255}, {"word": " tower,", "start": 1043.1, "end": 1043.46, "probability": 0.9956515431404114}, {"word": " the", "start": 1043.7, "end": 1043.76, "probability": 0.9838046431541443}, {"word": " speed", "start": 1043.76, "end": 1043.96, "probability": 0.9932268261909485}, {"word": " is", "start": 1043.96, "end": 1044.12, "probability": 0.9967605471611023}, {"word": " governed,", "start": 1044.12, "end": 1044.42, "probability": 0.9615305662155151}, {"word": " electrically", "start": 1044.8, "end": 1045.2, "probability": 0.9875947833061218}, {"word": " controlled.", "start": 1045.2, "end": 1045.76, "probability": 0.9903000593185425}, {"word": " Switches", "start": 1046.86, "end": 1047.02, "probability": 0.9652919173240662}, {"word": " direct", "start": 1047.02, "end": 1047.38, "probability": 0.9940100908279419}, {"word": " the", "start": 1047.38, "end": 1047.6, "probability": 0.9964488744735718}, {"word": " cars", "start": 1047.6, "end": 1047.82, "probability": 0.9979960918426514}, {"word": " to", "start": 1047.82, "end": 1048.06, "probability": 0.9971103668212891}, {"word": " the", "start": 1048.06, "end": 1048.18, "probability": 0.9961919784545898}, {"word": " right", "start": 1048.18, "end": 1048.34, "probability": 0.99623703956604}, {"word": " tracks,", "start": 1048.34, "end": 1048.86, "probability": 0.980749785900116}, {"word": " where", "start": 1048.98, "end": 1049.4, "probability": 0.9915673136711121}, {"word": " they", "start": 1049.4, "end": 1049.56, "probability": 0.9967485666275024}, {"word": " join", "start": 1049.56, "end": 1049.78, "probability": 0.9878815412521362}, {"word": " other", "start": 1049.78, "end": 1050.04, "probability": 0.9942517280578613}, {"word": " cars", "start": 1050.04, "end": 1050.34, "probability": 0.9977350234985352}, {"word": " to", "start": 1050.34, "end": 1050.58, "probability": 0.9746299982070923}, {"word": " make", "start": 1050.58, "end": 1050.72, "probability": 0.9989829659461975}, {"word": " new", "start": 1050.72, "end": 1050.98, "probability": 0.9920082092285156}, {"word": " trains", "start": 1050.98, "end": 1051.34, "probability": 0.9933850169181824}, {"word": " for", "start": 1051.34, "end": 1051.64, "probability": 0.9936011433601379}, {"word": " other", "start": 1051.64, "end": 1051.86, "probability": 0.9979159235954285}, {"word": " destinations.", "start": 1051.86, "end": 1052.5, "probability": 0.9943618774414062}]}, {"id": 89, "seek": 105250, "start": 1059.08, "end": 1068.64, "text": " We see the crate of machinery for South America going over the hump. The train in which this car arrived consists of cars bound for different destinations.", "tokens": [50413, 775, 766, 262, 27021, 286, 20230, 329, 2520, 2253, 1016, 625, 262, 49779, 13, 383, 4512, 287, 543, 428, 1097, 5284, 10874, 286, 5006, 5421, 329, 1180, 23982, 13, 51163], "temperature": 0.0, "avg_logprob": -0.08695605278015137, "compression_ratio": 1.4240506329113924, "no_speech_prob": 0.022785352542996407, "words": [{"word": " We", "start": 1059.08, "end": 1059.62, "probability": 0.39022916555404663}, {"word": " see", "start": 1059.62, "end": 1060.0, "probability": 0.9662836790084839}, {"word": " the", "start": 1060.0, "end": 1060.16, "probability": 0.9909263849258423}, {"word": " crate", "start": 1060.16, "end": 1060.34, "probability": 0.9307981729507446}, {"word": " of", "start": 1060.34, "end": 1060.48, "probability": 0.9931714534759521}, {"word": " machinery", "start": 1060.48, "end": 1060.84, "probability": 0.9829435348510742}, {"word": " for", "start": 1060.84, "end": 1061.14, "probability": 0.9762029051780701}, {"word": " South", "start": 1061.14, "end": 1061.34, "probability": 0.9789512753486633}, {"word": " America", "start": 1061.34, "end": 1061.84, "probability": 0.9951488375663757}, {"word": " going", "start": 1061.84, "end": 1062.24, "probability": 0.9455817937850952}, {"word": " over", "start": 1062.24, "end": 1062.52, "probability": 0.998388409614563}, {"word": " the", "start": 1062.52, "end": 1062.7, "probability": 0.9829897880554199}, {"word": " hump.", "start": 1062.7, "end": 1062.88, "probability": 0.4886639714241028}, {"word": " The", "start": 1063.84, "end": 1064.06, "probability": 0.9794257283210754}, {"word": " train", "start": 1064.06, "end": 1064.28, "probability": 0.9941853880882263}, {"word": " in", "start": 1064.28, "end": 1064.42, "probability": 0.9665789604187012}, {"word": " which", "start": 1064.42, "end": 1064.54, "probability": 0.9991053938865662}, {"word": " this", "start": 1064.54, "end": 1064.82, "probability": 0.9932704567909241}, {"word": " car", "start": 1064.82, "end": 1065.08, "probability": 0.9975997805595398}, {"word": " arrived", "start": 1065.08, "end": 1065.76, "probability": 0.8906509876251221}, {"word": " consists", "start": 1065.76, "end": 1066.5, "probability": 0.8790425658226013}, {"word": " of", "start": 1066.5, "end": 1066.76, "probability": 0.9982578158378601}, {"word": " cars", "start": 1066.76, "end": 1067.1, "probability": 0.9964955449104309}, {"word": " bound", "start": 1067.1, "end": 1067.46, "probability": 0.918199360370636}, {"word": " for", "start": 1067.46, "end": 1067.72, "probability": 0.9892411828041077}, {"word": " different", "start": 1067.72, "end": 1068.06, "probability": 0.972019612789154}, {"word": " destinations.", "start": 1068.06, "end": 1068.64, "probability": 0.9522131085395813}]}, {"id": 90, "seek": 105250, "start": 1069.76, "end": 1073.56, "text": " In the classification yard, it will join a train going to the harbor.", "tokens": [51213, 554, 262, 17923, 12699, 11, 340, 481, 4654, 257, 4512, 1016, 284, 262, 25451, 13, 51413], "temperature": 0.0, "avg_logprob": -0.08695605278015137, "compression_ratio": 1.4240506329113924, "no_speech_prob": 0.022785352542996407, "words": [{"word": " In", "start": 1069.76, "end": 1069.92, "probability": 0.9942803382873535}, {"word": " the", "start": 1069.92, "end": 1070.08, "probability": 0.9981362819671631}, {"word": " classification", "start": 1070.08, "end": 1070.56, "probability": 0.9891217350959778}, {"word": " yard,", "start": 1070.56, "end": 1071.28, "probability": 0.9978646636009216}, {"word": " it", "start": 1071.42, "end": 1071.92, "probability": 0.9937635064125061}, {"word": " will", "start": 1071.92, "end": 1072.06, "probability": 0.9815641045570374}, {"word": " join", "start": 1072.06, "end": 1072.28, "probability": 0.9978813529014587}, {"word": " a", "start": 1072.28, "end": 1072.42, "probability": 0.9890273809432983}, {"word": " train", "start": 1072.42, "end": 1072.7, "probability": 0.9974628686904907}, {"word": " going", "start": 1072.7, "end": 1073.0, "probability": 0.9914143681526184}, {"word": " to", "start": 1073.0, "end": 1073.2, "probability": 0.9972467422485352}, {"word": " the", "start": 1073.2, "end": 1073.34, "probability": 0.993794322013855}, {"word": " harbor.", "start": 1073.34, "end": 1073.56, "probability": 0.9586632251739502}]}, {"id": 91, "seek": 107356, "start": 1079.46, "end": 1094.7, "text": " Less than carload lots are reclassified as this LCL transfer. Just as whole trains must be rearranged with reference to the destinations of the cars, so must individual consignments of merchandise in a car be rearranged with reference to their destinations.", "tokens": [50363, 12892, 621, 1097, 2220, 6041, 389, 302, 31691, 355, 428, 406, 5097, 4351, 13, 2329, 355, 2187, 13404, 1276, 307, 37825, 5102, 351, 4941, 284, 262, 23982, 286, 262, 5006, 11, 523, 1276, 1981, 762, 570, 902, 286, 20813, 287, 257, 1097, 307, 37825, 5102, 351, 4941, 284, 511, 23982, 13, 51413], "temperature": 0.0, "avg_logprob": -0.07135268124667081, "compression_ratio": 1.7133333333333334, "no_speech_prob": 0.011909503489732742, "words": [{"word": " Less", "start": 1079.46, "end": 1080.1, "probability": 0.03815633803606033}, {"word": " than", "start": 1080.1, "end": 1080.28, "probability": 0.9375344514846802}, {"word": " carload", "start": 1080.28, "end": 1080.74, "probability": 0.7078655809164047}, {"word": " lots", "start": 1080.74, "end": 1081.02, "probability": 0.9569127559661865}, {"word": " are", "start": 1081.02, "end": 1081.2, "probability": 0.9738832712173462}, {"word": " reclassified", "start": 1081.2, "end": 1081.72, "probability": 0.9762618541717529}, {"word": " as", "start": 1081.72, "end": 1082.22, "probability": 0.5963696837425232}, {"word": " this", "start": 1082.22, "end": 1082.42, "probability": 0.951860785484314}, {"word": " LCL", "start": 1082.42, "end": 1083.38, "probability": 0.9496430456638336}, {"word": " transfer.", "start": 1083.38, "end": 1084.08, "probability": 0.8682183623313904}, {"word": " Just", "start": 1085.08, "end": 1085.34, "probability": 0.9862456321716309}, {"word": " as", "start": 1085.34, "end": 1085.54, "probability": 0.9954888224601746}, {"word": " whole", "start": 1085.54, "end": 1085.78, "probability": 0.9353273510932922}, {"word": " trains", "start": 1085.78, "end": 1086.14, "probability": 0.986275315284729}, {"word": " must", "start": 1086.14, "end": 1086.36, "probability": 0.9954853057861328}, {"word": " be", "start": 1086.36, "end": 1086.54, "probability": 0.9961826205253601}, {"word": " rearranged", "start": 1086.54, "end": 1087.08, "probability": 0.9930063188076019}, {"word": " with", "start": 1087.08, "end": 1087.28, "probability": 0.9944257736206055}, {"word": " reference", "start": 1087.28, "end": 1087.62, "probability": 0.9968506693840027}, {"word": " to", "start": 1087.62, "end": 1087.86, "probability": 0.9971666932106018}, {"word": " the", "start": 1087.86, "end": 1087.94, "probability": 0.9945005178451538}, {"word": " destinations", "start": 1087.94, "end": 1088.34, "probability": 0.9680899977684021}, {"word": " of", "start": 1088.34, "end": 1088.68, "probability": 0.9693616032600403}, {"word": " the", "start": 1088.68, "end": 1088.78, "probability": 0.9954386353492737}, {"word": " cars,", "start": 1088.78, "end": 1089.18, "probability": 0.9895862936973572}, {"word": " so", "start": 1089.7, "end": 1089.82, "probability": 0.9547987580299377}, {"word": " must", "start": 1089.82, "end": 1090.0, "probability": 0.9721572399139404}, {"word": " individual", "start": 1090.0, "end": 1090.5, "probability": 0.9735079407691956}, {"word": " consignments", "start": 1090.5, "end": 1091.22, "probability": 0.987462063630422}, {"word": " of", "start": 1091.22, "end": 1091.38, "probability": 0.9963834285736084}, {"word": " merchandise", "start": 1091.38, "end": 1091.7, "probability": 0.9902181029319763}, {"word": " in", "start": 1091.7, "end": 1092.02, "probability": 0.997222900390625}, {"word": " a", "start": 1092.02, "end": 1092.16, "probability": 0.984370768070221}, {"word": " car", "start": 1092.16, "end": 1092.38, "probability": 0.99898761510849}, {"word": " be", "start": 1092.38, "end": 1092.62, "probability": 0.9707401990890503}, {"word": " rearranged", "start": 1092.62, "end": 1093.24, "probability": 0.9944636821746826}, {"word": " with", "start": 1093.24, "end": 1093.44, "probability": 0.9946462512016296}, {"word": " reference", "start": 1093.44, "end": 1093.78, "probability": 0.9968851208686829}, {"word": " to", "start": 1093.78, "end": 1094.02, "probability": 0.9989169836044312}, {"word": " their", "start": 1094.02, "end": 1094.2, "probability": 0.9982024431228638}, {"word": " destinations.", "start": 1094.2, "end": 1094.7, "probability": 0.6363372206687927}]}, {"id": 92, "seek": 109470, "start": 1095.08, "end": 1105.66, "text": " And this is done here. The car is unloaded and the merchandise is reassembled in other cars. These cars are then attached to trains bound for many, many places.", "tokens": [50413, 843, 428, 318, 1760, 994, 13, 383, 1097, 318, 49975, 290, 262, 20813, 318, 302, 46826, 287, 584, 5006, 13, 2312, 5006, 389, 788, 7223, 284, 13404, 5421, 329, 867, 11, 867, 4113, 13, 50913], "temperature": 0.0, "avg_logprob": -0.0836660130818685, "compression_ratio": 1.645320197044335, "no_speech_prob": 0.12488637119531631, "words": [{"word": " And", "start": 1095.08, "end": 1095.68, "probability": 0.1333150565624237}, {"word": " this", "start": 1095.68, "end": 1095.88, "probability": 0.9575835466384888}, {"word": " is", "start": 1095.88, "end": 1096.1, "probability": 0.9943090677261353}, {"word": " done", "start": 1096.1, "end": 1096.32, "probability": 0.9879668354988098}, {"word": " here.", "start": 1096.32, "end": 1096.76, "probability": 0.9896911978721619}, {"word": " The", "start": 1097.7, "end": 1097.7, "probability": 0.713137149810791}, {"word": " car", "start": 1097.7, "end": 1097.88, "probability": 0.8873361349105835}, {"word": " is", "start": 1097.88, "end": 1098.02, "probability": 0.9485657215118408}, {"word": " unloaded", "start": 1098.02, "end": 1098.42, "probability": 0.9942737221717834}, {"word": " and", "start": 1098.42, "end": 1099.0, "probability": 0.6032227277755737}, {"word": " the", "start": 1099.0, "end": 1099.1, "probability": 0.9909776449203491}, {"word": " merchandise", "start": 1099.1, "end": 1099.48, "probability": 0.9850977659225464}, {"word": " is", "start": 1099.48, "end": 1099.74, "probability": 0.9820588231086731}, {"word": " reassembled", "start": 1099.74, "end": 1100.22, "probability": 0.9936397075653076}, {"word": " in", "start": 1100.22, "end": 1100.6, "probability": 0.9939714074134827}, {"word": " other", "start": 1100.6, "end": 1100.84, "probability": 0.997593104839325}, {"word": " cars.", "start": 1100.84, "end": 1101.22, "probability": 0.9819775223731995}, {"word": " These", "start": 1101.78, "end": 1102.04, "probability": 0.992920458316803}, {"word": " cars", "start": 1102.04, "end": 1102.32, "probability": 0.9970334768295288}, {"word": " are", "start": 1102.32, "end": 1102.52, "probability": 0.9894323348999023}, {"word": " then", "start": 1102.52, "end": 1102.64, "probability": 0.9952582716941833}, {"word": " attached", "start": 1102.64, "end": 1102.92, "probability": 0.9948286414146423}, {"word": " to", "start": 1102.92, "end": 1103.18, "probability": 0.9966866374015808}, {"word": " trains", "start": 1103.18, "end": 1103.64, "probability": 0.9930499792098999}, {"word": " bound", "start": 1103.64, "end": 1104.28, "probability": 0.8476499915122986}, {"word": " for", "start": 1104.28, "end": 1104.68, "probability": 0.9377084970474243}, {"word": " many,", "start": 1104.68, "end": 1104.98, "probability": 0.9990153312683105}, {"word": " many", "start": 1105.08, "end": 1105.18, "probability": 0.9996106028556824}, {"word": " places.", "start": 1105.18, "end": 1105.66, "probability": 0.9884623885154724}]}, {"id": 93, "seek": 109470, "start": 1107.92, "end": 1117.86, "text": " The engine house, where running repairs are made. We see another phase of railroading, maintenance of equipment. There are light repairs made at many points on the railroad.", "tokens": [51063, 383, 3113, 2156, 11, 810, 2491, 20097, 389, 925, 13, 775, 766, 1194, 7108, 286, 6787, 305, 4980, 11, 9262, 286, 5112, 13, 1318, 389, 1657, 20097, 925, 379, 867, 2173, 319, 262, 24337, 13, 51513], "temperature": 0.0, "avg_logprob": -0.0836660130818685, "compression_ratio": 1.645320197044335, "no_speech_prob": 0.12488637119531631, "words": [{"word": " The", "start": 1107.92, "end": 1108.54, "probability": 0.9680234789848328}, {"word": " engine", "start": 1108.54, "end": 1108.76, "probability": 0.9143054485321045}, {"word": " house,", "start": 1108.76, "end": 1109.14, "probability": 0.9935537576675415}, {"word": " where", "start": 1109.16, "end": 1109.34, "probability": 0.9841835498809814}, {"word": " running", "start": 1109.34, "end": 1109.62, "probability": 0.9919835925102234}, {"word": " repairs", "start": 1109.62, "end": 1110.04, "probability": 0.9957184195518494}, {"word": " are", "start": 1110.04, "end": 1110.28, "probability": 0.99601811170578}, {"word": " made.", "start": 1110.28, "end": 1110.6, "probability": 0.9992326498031616}, {"word": " We", "start": 1111.28, "end": 1111.52, "probability": 0.9974712133407593}, {"word": " see", "start": 1111.52, "end": 1111.7, "probability": 0.9980927109718323}, {"word": " another", "start": 1111.7, "end": 1112.0, "probability": 0.9792619943618774}, {"word": " phase", "start": 1112.0, "end": 1112.34, "probability": 0.9964959025382996}, {"word": " of", "start": 1112.34, "end": 1112.5, "probability": 0.998167872428894}, {"word": " railroading,", "start": 1112.5, "end": 1113.12, "probability": 0.9791031281153361}, {"word": " maintenance", "start": 1113.56, "end": 1113.82, "probability": 0.996246874332428}, {"word": " of", "start": 1113.82, "end": 1114.12, "probability": 0.9982748031616211}, {"word": " equipment.", "start": 1114.12, "end": 1114.62, "probability": 0.9954597353935242}, {"word": " There", "start": 1115.34, "end": 1115.5, "probability": 0.5582243204116821}, {"word": " are", "start": 1115.5, "end": 1115.62, "probability": 0.9398223161697388}, {"word": " light", "start": 1115.62, "end": 1115.8, "probability": 0.9016251564025879}, {"word": " repairs", "start": 1115.8, "end": 1116.24, "probability": 0.9967290163040161}, {"word": " made", "start": 1116.24, "end": 1116.54, "probability": 0.9963297247886658}, {"word": " at", "start": 1116.54, "end": 1116.66, "probability": 0.9775689244270325}, {"word": " many", "start": 1116.66, "end": 1116.86, "probability": 0.9975996613502502}, {"word": " points", "start": 1116.86, "end": 1117.16, "probability": 0.9916375279426575}, {"word": " on", "start": 1117.16, "end": 1117.34, "probability": 0.9948334693908691}, {"word": " the", "start": 1117.34, "end": 1117.46, "probability": 0.9983105659484863}, {"word": " railroad.", "start": 1117.46, "end": 1117.86, "probability": 0.8534127473831177}]}, {"id": 94, "seek": 111786, "start": 1121.16, "end": 1125.46, "text": " And there are heavy repairs, which are made in a great locomotive shop.", "tokens": [50363, 843, 612, 389, 4334, 20097, 11, 543, 389, 925, 287, 257, 1049, 33334, 19138, 6128, 13, 50713], "temperature": 0.0, "avg_logprob": -0.08990146662737872, "compression_ratio": 1.4752475247524752, "no_speech_prob": 0.01594988815486431, "words": [{"word": " And", "start": 1121.16, "end": 1121.8, "probability": 0.4126310348510742}, {"word": " there", "start": 1121.8, "end": 1122.26, "probability": 0.9670047760009766}, {"word": " are", "start": 1122.26, "end": 1122.44, "probability": 0.997198224067688}, {"word": " heavy", "start": 1122.44, "end": 1122.7, "probability": 0.9982426166534424}, {"word": " repairs,", "start": 1122.7, "end": 1123.2, "probability": 0.9949257373809814}, {"word": " which", "start": 1123.2, "end": 1123.44, "probability": 0.9981817007064819}, {"word": " are", "start": 1123.44, "end": 1123.58, "probability": 0.9930330514907837}, {"word": " made", "start": 1123.58, "end": 1123.76, "probability": 0.9984397292137146}, {"word": " in", "start": 1123.76, "end": 1123.92, "probability": 0.9867700338363647}, {"word": " a", "start": 1123.92, "end": 1124.08, "probability": 0.9760679602622986}, {"word": " great", "start": 1124.08, "end": 1124.42, "probability": 0.9603466987609863}, {"word": " locomotive", "start": 1124.42, "end": 1125.06, "probability": 0.9976653158664703}, {"word": " shop.", "start": 1125.06, "end": 1125.46, "probability": 0.9883179068565369}]}, {"id": 95, "seek": 111786, "start": 1129.0, "end": 1146.38, "text": " Here's a ponderous fantasy of fire and steel, the mighty forge of a modern Vulcan. All locomotives are overhauled periodically. Each one after going from 120,000 to 400,000 miles is sent to the shop for a complete overhauling.", "tokens": [50963, 3423, 338, 257, 37375, 516, 8842, 286, 2046, 290, 7771, 11, 262, 18680, 28325, 286, 257, 3660, 33402, 13, 1439, 33334, 313, 1083, 389, 18708, 276, 26034, 13, 5501, 530, 706, 1016, 422, 7982, 11, 830, 284, 7337, 11, 830, 4608, 318, 1908, 284, 262, 6128, 329, 257, 1844, 18708, 278, 13, 51763], "temperature": 0.0, "avg_logprob": -0.08990146662737872, "compression_ratio": 1.4752475247524752, "no_speech_prob": 0.01594988815486431, "words": [{"word": " Here's", "start": 1129.0, "end": 1131.56, "probability": 0.9024814069271088}, {"word": " a", "start": 1131.56, "end": 1131.68, "probability": 0.972513735294342}, {"word": " ponderous", "start": 1131.68, "end": 1132.26, "probability": 0.9957180917263031}, {"word": " fantasy", "start": 1132.26, "end": 1132.62, "probability": 0.9434457421302795}, {"word": " of", "start": 1132.62, "end": 1132.9, "probability": 0.9981083869934082}, {"word": " fire", "start": 1132.9, "end": 1133.3, "probability": 0.9965704679489136}, {"word": " and", "start": 1133.3, "end": 1133.56, "probability": 0.9982622265815735}, {"word": " steel,", "start": 1133.56, "end": 1133.96, "probability": 0.9951387643814087}, {"word": " the", "start": 1134.34, "end": 1134.48, "probability": 0.9603255391120911}, {"word": " mighty", "start": 1134.48, "end": 1134.8, "probability": 0.9984638690948486}, {"word": " forge", "start": 1134.8, "end": 1135.2, "probability": 0.9235906600952148}, {"word": " of", "start": 1135.2, "end": 1135.44, "probability": 0.9986000657081604}, {"word": " a", "start": 1135.44, "end": 1135.58, "probability": 0.9909541010856628}, {"word": " modern", "start": 1135.58, "end": 1135.92, "probability": 0.9990929365158081}, {"word": " Vulcan.", "start": 1135.92, "end": 1136.28, "probability": 0.9659356474876404}, {"word": " All", "start": 1137.36, "end": 1137.68, "probability": 0.996967613697052}, {"word": " locomotives", "start": 1137.68, "end": 1138.28, "probability": 0.9985360900561014}, {"word": " are", "start": 1138.28, "end": 1138.48, "probability": 0.998687207698822}, {"word": " overhauled", "start": 1138.48, "end": 1139.7, "probability": 0.9697069525718689}, {"word": " periodically.", "start": 1139.7, "end": 1139.7, "probability": 0.9921095967292786}, {"word": " Each", "start": 1140.42, "end": 1140.62, "probability": 0.9984502792358398}, {"word": " one", "start": 1140.62, "end": 1140.86, "probability": 0.9983524084091187}, {"word": " after", "start": 1140.86, "end": 1141.1, "probability": 0.520629346370697}, {"word": " going", "start": 1141.1, "end": 1141.46, "probability": 0.9966601133346558}, {"word": " from", "start": 1141.46, "end": 1141.7, "probability": 0.9965769648551941}, {"word": " 120", "start": 1141.7, "end": 1142.28, "probability": 0.954590916633606}, {"word": ",000", "start": 1142.28, "end": 1142.88, "probability": 0.9897470474243164}, {"word": " to", "start": 1142.88, "end": 1143.06, "probability": 0.992156982421875}, {"word": " 400", "start": 1143.06, "end": 1143.32, "probability": 0.9967014193534851}, {"word": ",000", "start": 1143.32, "end": 1143.9, "probability": 0.9973655343055725}, {"word": " miles", "start": 1143.9, "end": 1144.18, "probability": 0.9986961483955383}, {"word": " is", "start": 1144.18, "end": 1144.4, "probability": 0.7087660431861877}, {"word": " sent", "start": 1144.4, "end": 1144.58, "probability": 0.9931756854057312}, {"word": " to", "start": 1144.58, "end": 1144.74, "probability": 0.9924880266189575}, {"word": " the", "start": 1144.74, "end": 1144.84, "probability": 0.9970176219940186}, {"word": " shop", "start": 1144.84, "end": 1145.04, "probability": 0.9980295300483704}, {"word": " for", "start": 1145.04, "end": 1145.26, "probability": 0.9979487061500549}, {"word": " a", "start": 1145.26, "end": 1145.36, "probability": 0.9660146236419678}, {"word": " complete", "start": 1145.36, "end": 1145.68, "probability": 0.9997637867927551}, {"word": " overhauling.", "start": 1145.68, "end": 1146.38, "probability": 0.9916405975818634}]}, {"id": 96, "seek": 129638, "start": 1298.04, "end": 1309.64, "text": " The slip track is an oil track where overhauled locomotives get final tests. They can be driven many miles at all speeds forward and backward on a track that simulates conditions of speed.", "tokens": [50413, 383, 13819, 2610, 318, 281, 3056, 2610, 810, 18708, 276, 33334, 313, 1083, 651, 2457, 5254, 13, 1119, 460, 307, 7986, 867, 4608, 379, 477, 12055, 2651, 290, 19528, 319, 257, 2610, 326, 985, 15968, 3403, 286, 2866, 13, 51013], "temperature": 0.0, "avg_logprob": -0.06813827793249923, "compression_ratio": 1.6822033898305084, "no_speech_prob": 0.010170713998377323, "words": [{"word": " The", "start": 1298.04, "end": 1298.64, "probability": 0.9039047956466675}, {"word": " slip", "start": 1298.64, "end": 1298.88, "probability": 0.8296089768409729}, {"word": " track", "start": 1298.88, "end": 1299.26, "probability": 0.9084669947624207}, {"word": " is", "start": 1299.26, "end": 1299.62, "probability": 0.9927230477333069}, {"word": " an", "start": 1299.62, "end": 1299.78, "probability": 0.9938691258430481}, {"word": " oil", "start": 1299.78, "end": 1300.02, "probability": 0.9991334080696106}, {"word": " track", "start": 1300.02, "end": 1300.52, "probability": 0.9911836385726929}, {"word": " where", "start": 1300.52, "end": 1301.36, "probability": 0.6760706901550293}, {"word": " overhauled", "start": 1301.36, "end": 1301.92, "probability": 0.523085467517376}, {"word": " locomotives", "start": 1301.92, "end": 1302.42, "probability": 0.9992910027503967}, {"word": " get", "start": 1302.42, "end": 1302.68, "probability": 0.9934932589530945}, {"word": " final", "start": 1302.68, "end": 1303.1, "probability": 0.9925265312194824}, {"word": " tests.", "start": 1303.1, "end": 1303.48, "probability": 0.9268658757209778}, {"word": " They", "start": 1304.18, "end": 1304.36, "probability": 0.9944257736206055}, {"word": " can", "start": 1304.36, "end": 1304.52, "probability": 0.9987277388572693}, {"word": " be", "start": 1304.52, "end": 1304.64, "probability": 0.9986587762832642}, {"word": " driven", "start": 1304.64, "end": 1304.82, "probability": 0.9977738261222839}, {"word": " many", "start": 1304.82, "end": 1305.12, "probability": 0.9986745119094849}, {"word": " miles", "start": 1305.12, "end": 1305.46, "probability": 0.9989000558853149}, {"word": " at", "start": 1305.46, "end": 1305.64, "probability": 0.43713808059692383}, {"word": " all", "start": 1305.64, "end": 1305.9, "probability": 0.9984742999076843}, {"word": " speeds", "start": 1305.9, "end": 1306.24, "probability": 0.9897845387458801}, {"word": " forward", "start": 1306.24, "end": 1306.66, "probability": 0.8852903842926025}, {"word": " and", "start": 1306.66, "end": 1306.9, "probability": 0.9969125986099243}, {"word": " backward", "start": 1306.9, "end": 1307.22, "probability": 0.9784931540489197}, {"word": " on", "start": 1307.22, "end": 1307.58, "probability": 0.9677762389183044}, {"word": " a", "start": 1307.58, "end": 1307.7, "probability": 0.996052622795105}, {"word": " track", "start": 1307.7, "end": 1307.9, "probability": 0.9937120676040649}, {"word": " that", "start": 1307.9, "end": 1308.12, "probability": 0.9975795149803162}, {"word": " simulates", "start": 1308.12, "end": 1308.6, "probability": 0.9948006570339203}, {"word": " conditions", "start": 1308.6, "end": 1309.1, "probability": 0.9920652508735657}, {"word": " of", "start": 1309.1, "end": 1309.34, "probability": 0.9981591105461121}, {"word": " speed.", "start": 1309.34, "end": 1309.64, "probability": 0.998613715171814}]}, {"id": 97, "seek": 129638, "start": 1310.48, "end": 1324.74, "text": " A monster locomotive thoroughly overhauled is a symbol of that factor so vital in all mechanics, all industry, maintenance. 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Everything possible is saved and put away for future use. 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