The 2019 research conducted by Dr. Maria Santos examining Antarctic ice core specimens represented one of the earliest investigations to...
GMAT Craft and Structure : (Structure) Questions
The 2019 research conducted by Dr. Maria Santos examining Antarctic ice core specimens represented one of the earliest investigations to utilize machine learning algorithms for analyzing paleoclimate information. Throughout this investigation, Santos utilized artificial intelligence techniques to discover atmospheric composition patterns that had remained undetectable through prior methods, spanning a temporal range of 50,000 years. This novel methodology uncovered climate variations that conventional statistical techniques had failed to detect, yielding fresh perspectives on prehistoric weather patterns. The methodological framework developed by Santos illustrates how computational instruments could transform scientists' analysis of historical climate information, a perspective she has championed across her continuing research endeavors.
Which option most accurately identifies the primary objective of the passage?
To illustrate Santos's implementation of computational techniques in paleoclimate investigation
To contend that machine learning algorithms outperform conventional statistical approaches in climate science
To clarify how Santos's 2019 investigation motivated fellow researchers to embrace comparable methodological strategies
To propose that Santos's identified patterns derived from climate data she had examined in earlier work
Step 1: Decode and Map the Passage
Create Passage Analysis Table
| Text from Passage | Analysis |
|---|---|
| "The 2019 research conducted by Dr. Maria Santos examining Antarctic ice core specimens represented one of the earliest investigations to utilize machine learning algorithms for analyzing paleoclimate information." |
|
| "Throughout this investigation, Santos utilized artificial intelligence techniques to discover atmospheric composition patterns that had remained undetectable through prior methods, spanning a temporal range of 50,000 years." |
|
| "This novel methodology uncovered climate variations that conventional statistical techniques had failed to detect, yielding fresh perspectives on prehistoric weather patterns." |
|
| "The methodological framework developed by Santos illustrates how computational instruments could transform scientists' analysis of historical climate information, a perspective she has championed across her continuing research endeavors." |
|
Provide Passage Architecture & Core Elements
Main Point: The passage describes how Dr. Santos's 2019 research demonstrated the transformative potential of using machine learning techniques to analyze paleoclimate data.
Argument Flow: The passage opens by establishing Santos's research as pioneering in applying machine learning to paleoclimate analysis. It then details what her AI techniques accomplished—discovering previously undetectable atmospheric patterns spanning 50,000 years that conventional methods had missed. Finally, it positions her work as illustrating the broader transformative potential of computational tools in climate science, noting her continued advocacy for this approach.
Step 2: Interpret the Question Precisely
This is a fill-in-the-blank question asking us to choose the best logical connector. The answer must create the right relationship between what comes before and after the blank.
Step 3: Prethink the Answer
- The passage focuses on Santos's specific research—her 2019 use of machine learning for ice core analysis
- We learn what she did (applied AI techniques), what she found (atmospheric patterns over 50,000 years), and why it mattered (discovered things conventional methods missed)
- The passage concludes by noting how her framework shows the transformative potential of computational tools and that she continues to advocate for this approach
- The right answer should capture that the passage is primarily about describing/illustrating Santos's pioneering use of computational techniques in paleoclimate research
To illustrate Santos's implementation of computational techniques in paleoclimate investigation
✓ Correct
- Correct - Matches our analysis perfectly - the passage illustrates Santos's implementation of computational techniques (ML/AI) in paleoclimate investigation
- Captures both the specific focus (Santos's work) and the method (computational techniques)
- Aligns with how the passage presents her research as demonstrating the potential of these approaches
To contend that machine learning algorithms outperform conventional statistical approaches in climate science
✗ Incorrect
- Incorrect - While the passage mentions that Santos's methods found things conventional statistical approaches missed, it doesn't make a broad argument that ML algorithms outperform conventional approaches
- The passage is descriptive about Santos's specific work rather than argumentative about method superiority
- What trap this represents: Students might conflate mentioning an advantage with making a comparative argument
To clarify how Santos's 2019 investigation motivated fellow researchers to embrace comparable methodological strategies
✗ Incorrect
- Incorrect - The passage never discusses how Santos's investigation motivated other researchers or their adoption of similar strategies
- This choice introduces information not present in the passage
- What trap this represents: Students might assume that pioneering research automatically leads to widespread adoption by others
To propose that Santos's identified patterns derived from climate data she had examined in earlier work
✗ Incorrect
- Incorrect - The passage doesn't suggest Santos's patterns came from earlier work - it presents the 2019 research as discovering new patterns
- This misrepresents the source and novelty of her findings