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Paper Citation Record · LEDGER

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models

As of 17 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 2 inbound Pith citation observations for arXiv:2412.05587.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.05587 v2

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:37:54.102557Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:30:40.726787Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-15T16:24:25.519478Z

Reference resolution

7 of 7 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 52eee53e-c05b-43cc-8691-66dd4f559ba3 · outbound

This paper cites operators,.

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models operators,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:37:54.270335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T20:37:54.061503Z digest=sha256:8c4d30cd4d947a1f9de4e41e03d0a3032cd65d3e81912273019c9be00e257b1b

Observation 14c2145a-e2f1-4638-8dfe-8edaf45fa7af · outbound

This paper cites knowledge hallucination,.

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models knowledge hallucination,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:37:54.251054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T20:37:54.067705Z digest=sha256:72e7f44fb24336f4100812c0c43a0a22fc10de0f2c0dfb829d0b069b07163bf4

Observation d9f979e0-af79-4d4c-96eb-d5bca2aca9d9 · outbound

This paper cites Google Earth Engine (GEE).

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models Google Earth Engine (GEE)

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:37:54.225766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T20:37:54.073462Z digest=sha256:fe91f3688c1cdc467a1812645deae648dfc11bee0417c7ff1730c9a2dc6771d4

Observation a63b0397-7365-46b7-b139-41d869d28ff0 · outbound

This paper cites an unresolved cited work.

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-11T20:37:54.203385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T20:37:54.080904Z digest=sha256:4ab795cbfd2098bd0c0ba5e43e652a036a8e2f4eabb2ad52072b091c42be068e

Observation 14e1cc24-1baf-4531-835b-05a9e20f52d4 · outbound

This paper cites Augmenting LLMs with Knowledge: A survey on hallucination prevention.

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models Augmenting LLMs with Knowledge: A survey on hallucination prevention

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T20:37:54.089159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:37:54.089159Z digest=sha256:65890d54918499f86fa39dfee621b53d4d163eed254c4d7de252d86b9e81912a

Observation 1fd6b54d-a56b-4e35-8f36-205bd6f3cf0d · outbound

This paper cites Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey.

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T20:37:54.102557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:37:54.102557Z digest=sha256:790481d4ddb91f72b1be4656f27c35e6def81f791c9aed2b02bc56a21c3076d7

Observation 3f49c9ca-e82e-4dad-ad40-fbca0571d6ec · outbound

This paper cites Fine-tuning and Utilization Methods of Domain-specific LLMs.

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models Fine-tuning and Utilization Methods of Domain-specific LLMs

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-11T20:37:54.096111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:37:54.096111Z digest=sha256:e6fcb2eb851b49fbd347298e08f03e1c3deefb09c523d9ebe6f1bd83184a5e3c

Pith citing papers

Observation c334f4f9-f099-4c32-a340-07cf845a81f8 · inbound

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models cites this paper.

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T20:30:40.726787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:30:40.726787Z digest=sha256:b4befb4956a571ae7815ffd3a10d7508fa746420b53d6c0f6b88050fdd789dc3

Observation 49780fc6-ee03-4e7e-a2fe-91908697623b · inbound

GeoAnalystBench: A GeoAI benchmark for assessing large language models for spatial analysis workflow and code generation cites this paper.

GeoAnalystBench: A GeoAI benchmark for assessing large language models for spatial analysis workflow and code generation GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-15T16:24:25.525278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T16:24:25.083653Z digest=sha256:f7734bfdaf46b5d4012a346374215b87adcf4c632633eb378ee7385883a77bd9