영어 모의고사 (자동 편성)

Athletes preparing for major endurance events sometimes ①trains for weeks at high altitude, where the air contains less oxygen than at sea level, in hopes of gaining a physiological edge once they return to compete at lower elevations. In this thin air, the body responds by producing more red blood cells, ②which carry oxygen more efficiently through the bloodstream to working muscles. When these athletes return to sea level, where oxygen is more abundant, their blood ③retains this elevated capacity for a limited period, potentially translating into improved endurance performance. However, the benefits of altitude training are far from guaranteed, since individual athletes respond quite differently to the same conditions, and some experience excessive fatigue that ④undermines the very training they hoped to complete. Many elite programs therefore follow a strategy known as live high, train low, in which athletes sleep at altitude to stimulate blood adaptations but perform intense workouts at lower elevation ⑤to maintain quality and intensity.

A growing number of health apps now track steps, sleep, and heart rate throughout the day, ①quietly building a detailed picture of a user's physical condition without requiring a single visit to a doctor's office. By comparing this stream of data against patterns drawn from millions of other users, the app's algorithm can flag early warning signs, such as an irregular heartbeat, long before the person ②experiencing it would have noticed anything unusual on their own. For people living far from specialists or unable to afford frequent checkups, this kind of constant monitoring can ③feel like a genuine safety net. Doctors caution, however, that these apps ④are designed to detect patterns, not to diagnose illness, and that a worried user should always confirm any alarming reading with a professional. Treating a wellness app as a substitute for medical expertise, they warn, can ⑤being just as risky as ignoring a warning altogether.

Imagine two factories ①making the same product: one in a country with strict carbon rules, and one in a country with almost none. The factory facing stricter rules often spends more, which can make its goods pricier than those ②made elsewhere. To fix this imbalance, some governments have introduced the carbon border adjustment mechanism, a policy charging imported goods a fee based on how much carbon ③were released while producing them. Supporters argue that the system protects domestic industries and ④pushes foreign manufacturers toward cleaner methods. However, critics claim it unfairly burdens developing countries, which often lack money to modernize factories quickly. For example, a small exporter in a poorer nation might struggle to pay the added charge, though it contributes little to global emissions. Still, if wealthier nations pair the policy with technical support, it could become a genuinely fair tool for ⑤cutting emissions worldwide.

Ethical consumption has placed new pressure on companies to justify their practices publicly. (A) Yet critics point out that such reports are sometimes little more than carefully worded public relations documents. (B) In response, many corporations now publish detailed reports describing their environmental and labor practices. (C) For this reason, many experts insist that independent audits are necessary to confirm whether ethical claims are genuine.

Only a decade ago, translation apps produced sentences so awkward that users often laughed at the results rather than trusting them. (A) Frequent travelers now point their phone cameras at street signs and receive an instant translation overlaid on the screen, thanks to this leap in accuracy. (B) Even so, the technology still struggles with humor, sarcasm, and cultural nuance, areas where a single wrong word can completely change the intended meaning. (C) Today, many of these apps rely on neural networks that analyze entire sentences at once, capturing context instead of translating word by word.

A navigation app calculating a route rarely relies on distance alone; instead, it constantly weighs real-time traffic reports, past congestion patterns, and even data from other drivers' phones currently on the road. (A) Residents of these once-quiet neighborhoods have increasingly complained about the sudden surge of unfamiliar traffic, arguing that the algorithm can end up creating a new problem for the wider community. (B) The convenience comes at a cost that few passengers consider, however, since redirecting thousands of drivers onto the same shortcut can make a quiet side street as congested as the highway it was meant to help travelers avoid. (C) This flood of information allows the app to reroute a driver away from a sudden accident within seconds, often before the driver has any idea the accident occurred at all.

주어진 문장: Some researchers even suggest that painting rooftops white could further help reflect sunlight away from buildings. On a summer evening, downtown streets often feel noticeably hotter than nearby parks or suburban neighborhoods, even after the sun has set. ( ① ) This phenomenon, known as the urban heat island effect, occurs when cities retain more heat than surrounding rural areas because of their dense concentration of asphalt, concrete, and buildings. ( ② ) Unlike soil or vegetation, which absorb and release heat gradually, these man-made surfaces absorb sunlight during the day and slowly radiate it back at night, preventing temperatures from cooling. ( ③ ) Tall buildings packed closely together also block wind, trapping warm air within narrow streets. ( ④ ) In contrast, areas with abundant trees and open water naturally stay cooler, since plants release moisture that helps lower surrounding temperatures. To reduce this effect, many cities have begun installing rooftop gardens and expanding public parks, hoping that additional greenery will absorb less heat than pavement does. ( ⑤ )

Whenever a user marks a message as spam or rescues a message mistakenly filtered out, that action becomes new training data, sharpening the filter's future decisions. Every day, email providers quietly block billions of unwanted messages before they ever reach a user's inbox, a task that would be impossible without an AI filtering system running constantly in the background. ( ① ) The filter examines each incoming message for suspicious patterns, including certain keywords, unusual sender addresses, and formatting tricks that scammers commonly rely on to slip past detection. ( ② ) What makes the system effective is that it keeps learning after launch. ( ③ ) This creates a constant back-and-forth, since spammers study which messages get blocked and then adjust their wording to slip through again. ( ④ ) As a result, spam filtering is less like a fixed wall and more like an ongoing contest, with each side continuously adapting to outsmart the other. ( ⑤ )

This constant, individualized adjustment is what makes the technology feel so different from a standard workbook. Adaptive learning apps promise something no traditional classroom can easily offer: a lesson plan that adjusts itself to each individual student in real time. ( ① ) As a student answers practice questions, the app tracks which concepts are mastered and which remain shaky, then quietly reshuffles the next set of problems to target the weaker areas. ( ② ) Early studies suggest that this personalized pacing can help struggling students catch up faster than a one-size-fits-all worksheet ever could. ( ③ ) However, critics caution that an app cannot replace the encouragement, humor, and flexibility a human teacher brings to a lesson, especially when a student is frustrated rather than simply behind. ( ④ ) There is also a subtler concern: students who grow used to instant, algorithm-generated feedback may struggle later with the slower, more ambiguous kind of feedback that real-world tasks and mentors typically provide. ( ⑤ )

Unlike a static list of best-sellers, this assistant can adjust its suggestions on the spot, responding to follow-up questions the way a knowledgeable salesperson might in a physical store. Browsing an online store today often means chatting with an AI assistant that asks a few quick questions, such as budget or intended use, before suggesting a short list of products tailored to the answers. ( ① ) Retailers report that shoppers who use these chatbots tend to complete purchases more often and return fewer items, since the guided conversation helps buyers choose products that actually fit their needs. ( ② ) Some shoppers, however, remain wary of how personal the questions can feel. ( ③ ) They wonder how much of that conversation is quietly stored and reused to influence future purchases. ( ④ ) Consumer advocates argue that stores should clearly explain what happens to this data, rather than burying the explanation in a lengthy privacy policy that almost no one reads. ( ⑤ )