Cooperative Agreement for CESU-affiliated Partner with Californian Cooperative Ecosystem Studies Unit | G24AS00385

Grant Opportunity FAQs (USGS Funding Opportunity Number G24AS00385)

What is the funding opportunity number for this grant?

The Funding Opportunity Number (FON) is G24AS00385.

Which federal agency is offering this opportunity?

This opportunity is offered by the U.S. Geological Survey (USGS).

What type of award is being offered?

The funding is structured as a cooperative agreement. That means the project is expected to be carried out with substantial involvement from USGS staff, including collaboration, coordination, and iterative technical engagement, rather than being a fully independent award.

What program framework is this opportunity offered through?

It is offered through the Cooperative Ecosystem Studies Unit (CESU) framework, which connects federal agencies with partner institutions to support applied research, technical assistance, and education aligned to public resource management and science needs.

Which CESU network is this opportunity restricted to?

Eligibility is limited to participating partners of the Californian Cooperative Ecosystem Studies Unit (CESU) Program.

Is this an open competition for any university or organization?

No. Based on the opportunity description, it is not open to all institutions. Only organizations that are participating partners of the Californian CESU are eligible to apply.

What is the CFDA number associated with this opportunity?

The opportunity is listed under CFDA 15.808.

What activity category does this opportunity fall under?

It is categorized under Science and Technology and other Research and Development.

What is the main research focus of this funding call?

The core focus is research on using artificial intelligence that is informed by explicit semantics to improve how USGS conducts scientific assessments. In practice, this points toward AI approaches that incorporate structured meaning (not only pattern recognition or black-box generation) to support defensible, traceable, and up-to-date assessments.

What does "AI informed by explicit semantics" mean in this context?

In this opportunity, "explicit semantics" refers to structured representations of meaning such as formal ontologies, knowledge graphs, controlled vocabularies, and explicit representations of relationships among concepts, data sources, and evidence. The intent is to make AI-assisted outputs more interpretable and easier to audit back to sources.

Why is USGS emphasizing semantics-aware AI for assessments?

USGS assessments in areas such as energy resources, minerals, biodiversity, and other national natural resource assets are often legislatively mandated and must be defensible, traceable, and current with the body of available knowledge. The opportunity notes that the volume and pace of information have become difficult to manage using traditional workflows, and semantics-aware AI is being pursued to improve currency, consistency, and transparency.

What are "AI scientists" as described in the opportunity?

"AI scientists" are described as intelligent agents operating within a technology framework that can iteratively improve as generative AI and related tools advance. The intent is not a one-time model build, but an approach that can be repeatedly updated across new generations of models and refined through ongoing interaction with USGS scientists.

Does this opportunity expect a human-in-the-loop approach?

Yes. The description implies a human-in-the-loop design where USGS subject matter experts regularly guide the system, correct it, and help it learn USGS-specific standards for evidence, uncertainty, terminology, and assessment practices.

What kinds of assessment workflow support does USGS appear to be seeking?

The description suggests deliverables that support assessment workflows such as literature and data discovery, extraction and summarization of findings with provenance, mapping claims to evidence, identifying gaps or inconsistencies, tracking updates over time, and producing structured outputs that can feed into reports while maintaining an auditable chain from conclusions back to source material.

What is the maximum award amount (award ceiling)?

The award ceiling is $499,999.

How many awards will USGS make under this opportunity?

The provided opportunity text does not specify the number of expected awards.

When was this opportunity created?

The opportunity was created on 2024-06-05.

What is the application closing date?

The original application closing date is 2024-07-15.

What does the "eligible applicant category: Others" mean here?

In this listing, "Others" reflects that CESU partnerships can include universities, research organizations, and other qualified entities that are formal CESU members. Eligibility is still restricted to participating partners of the Californian CESU.

What should applicants expect because the award is a cooperative agreement?

Applicants should expect coordination requirements and active collaboration with USGS, including shared project planning, regular technical check-ins, and iterative development aligned to real USGS assessment needs.

Is the goal to build a single, static AI model?

No. The opportunity emphasizes an approach that can be updated and improved repeatedly as new generations of generative AI tools emerge, with ongoing refinement through adaptive interaction with USGS scientists.

What is the overall purpose of this opportunity?

The overall aim is to accelerate and improve the rigor of USGS scientific assessments by combining generative AI with explicit semantic structures so that AI-assisted outputs are more interpretable, traceable, and usable in high-stakes public resource decision contexts.

Does the description indicate what project scale USGS has in mind?

While the number of awards is not specified, the $499,999 ceiling suggests a mid-sized applied research effort suited to building and demonstrating a working framework, prototype, or pilot capability rather than a large multi-year program.