Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
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Page Freshness
Canonical route: /signal-canvas/geoai-agency-primitives
This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.
Agent Handoff
Canonical ID geoai-agency-primitives | Route /signal-canvas/geoai-agency-primitives
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/geoai-agency-primitivesMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "geoai-agency-primitives",
"query_text": "Summarize GeoAI Agency Primitives"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "GeoAI Agency Primitives",
"normalized_query": "2604.01869",
"route": "/signal-canvas/geoai-agency-primitives",
"paper_ref": "geoai-agency-primitives",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 8
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: GeoAI Agency Primitives
PDF: https://arxiv.org/pdf/2604.01869v1
Source count: Pending verification
Coverage: 33%
Last proof check: 2026-04-03T20:50:40.576Z
Signal Canvas receipt window
/buildability/geoai-agency-primitives
Subject: GeoAI Agency Primitives
Verdict
Watch
Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Preparing verified analysis
Dimensions overall score 7.0
No public code linked for this paper yet.
these capabilities have not translated into productivity gains for practitioners who spend most of their time producing vector layers, raster maps, and cartographic products
Directly stated in the abstract as a key problem statement
partial
The gap is not model capability alone but the absence of an agency layer that supports iterative collaboration
Directly stated in abstract as a core argument
partial
We propose a vocabulary of $9$ primitives for such a layer
Explicitly stated with specific number in abstract
partial
including navigation, perception, geo-referenced memory, and dual modeling
Directly listed in abstract with specific examples
partial
along with a benchmark that measures human productivity
Directly stated in abstract as part of the proposed approach
partial
practitioners who spend most of their time producing vector layers, raster maps, and cartographic products
Directly stated in abstract as background context
partial
Our goal is a vocabulary that makes agentic assistance in GIS implementable, testable, and comparable
Explicitly stated as the research goal in abstract
partial
core capabilities that connect Foundation models to the artifact-centric, human-in-the-loop workflows where GIS practitioners actually work
Directly stated in abstract as the core research premise
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
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Receipt path
/buildability/geoai-agency-primitives
Paper ref
geoai-agency-primitives
arXiv id
2604.01869
Generated at
2026-04-03T20:50:40.576Z
Evidence freshness
stale
Last verification
2026-04-03T20:50:40.576Z
Sources
0
References
0
Coverage
33%
Lineage hash
f8e8258fea84d0763e583e83a652ee6dc7b283c286c7ceda49d2522c4fa1c104
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Verification pending / evidence receipt incomplete
repo_url
references