[
  {
    "description": "A metric developed for quantifying the progression and emergence velocity of scientific technologies and methodologies within a research corpus. Used to identify which technologies are gaining traction and forecast their trajectory based on publication patterns over time.",
    "kgmid": "",
    "sameAs": "",
    "termName": "Rate of Rise",
    "usage": "used extensively",
    "year": "2024"
  },
  {
    "description": "A pragmatic engineering philosophy that resists the tendency to treat every problem as unique and requiring bespoke solutions. Emphasizes pattern recognition across domains and matching established tools to problems rather than reinventing approaches. Serves as a counterweight to technology hype and over-engineering.",
    "kgmid": "",
    "sameAs": "",
    "termName": "Not Everything is a Snowflake",
    "usage": "used extensively",
    "year": "2020"
  },
  {
    "description": "An analytical approach that applies data science and NLP methods to scientific literature itself, treating the corpus of published research as a dataset to be mined for trends, patterns, and forecasts about the evolution of scientific fields.",
    "kgmid": "",
    "sameAs": "",
    "termName": "Science-of-Science",
    "usage": "used extensively",
    "year": "2024"
  },
  {
    "description": "A distinction between two types of domain expertise: system experts possess deep understanding of underlying mechanisms and can reason about novel situations, while practice experts have accumulated wisdom through experience but may struggle with unfamiliar scenarios. This distinction informs the design of knowledge assessment instruments and training systems.",
    "kgmid": "",
    "sameAs": "",
    "termName": "System Expert vs. Practice Expert",
    "usage": "used extensively",
    "year": "2016"
  },
  {
    "description": "The degree to which visual and sensory cues in a simulation accurately represent their real-world counterparts. Critical for ensuring that simulator-trained behaviors transfer to actual operational contexts. Requires systematic validation through user studies with domain experts.",
    "kgmid": "",
    "sameAs": "",
    "termName": "Cue Fidelity",
    "usage": "used extensively",
    "year": "2019"
  }
]