Paper Citation Record · LEDGER

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives

As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.29064.

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

pith.paper-citation-record.v1
2607.29064 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T14:22:25.337039Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

verified exact1
verified fuzzy0
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bac597ef-69f5-4c2c-a3e1-5e3574ae6e3f · outbound

This paper cites Investigating the nature and impact of reporting bias in road crash data,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Investigating the nature and impact of reporting bias in road crash data,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:24.198623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3b18ea5-b9cc-4d81-b024-4ee8be3d9634 · outbound

This paper cites Under-reporting of motor vehicle traffic crash victims in New Zealand,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Under-reporting of motor vehicle traffic crash victims in New Zealand,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:24.339652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1e51048-f7a8-438c-a253-41484c302a76 · outbound

This paper cites Under-reporting of road crash casualties in France,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Under-reporting of road crash casualties in France,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:24.419497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01c6c53b-9799-4f2c-8515-7346e0b87c7b · outbound

This paper cites Crash data quality for road safety research: Current state and future directions,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Crash data quality for road safety research: Current state and future directions,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:24.550619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04f910fa-39f5-4692-8c1a-d0a9bc30b109 · outbound

This paper cites Understanding traffic crash under-reporting: linking police and medical records to individual and crash characteristics,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Understanding traffic crash under-reporting: linking police and medical records to individual and crash characteristics,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:24.725502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e9a27ac-bf47-4428-a59b-bbdbc4927440 · outbound

This paper cites Protected Bike Lanes Are Not Created Equal: A Review of Design, Safety, and Mobility Outcomes,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Protected Bike Lanes Are Not Created Equal: A Review of Design, Safety, and Mobility Outcomes,

Reference 6

Resolution: verified exact; doi, observed 2026-08-03T14:24:20.868944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e8effe25-8ce5-4abe-b395-919cb8e72475 · outbound

This paper cites Semantic search approach for information extraction from traffic crash narratives,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Semantic search approach for information extraction from traffic crash narratives,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:24.848158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 347bd6c9-797d-4269-8807-569239851f58 · outbound

This paper cites Application of text mining techniques to identify actual wrong-way driving (WWD) crashes in police reports,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Application of text mining techniques to identify actual wrong-way driving (WWD) crashes in police reports,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:24.932292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbe4793d-ee1f-4368-b701-7725007693b6 · outbound

This paper cites Identification and analysis of misclassified work-zone crashes using text mining techniques,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Identification and analysis of misclassified work-zone crashes using text mining techniques,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:24.994390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99488de3-b309-48a9-bb6b-729ef9b51975 · outbound

This paper cites Natural language understanding in road accident data analysis,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Natural language understanding in road accident data analysis,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.044364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3454bbf4-7cff-4d40-9cd2-9a9d317ba0fb · outbound

This paper cites Identifying secondary crashes using text mining techniques,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Identifying secondary crashes using text mining techniques,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.101511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a3db5fc-73b9-4312-bdb7-47436493c14f · outbound

This paper cites Large language models and their applications in roadway safety and mobility enhancement: A comprehensive review,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Large language models and their applications in roadway safety and mobility enhancement: A comprehensive review,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.183555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5c69e96-19d5-4399-997a-352831424eee · outbound

This paper cites Leveraging Large Language Models for advanced analysis of crash narratives in traffic safety research.,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Leveraging Large Language Models for advanced analysis of crash narratives in traffic safety research.,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.237968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 742b89bc-93ba-41c2-8ed6-90d12fdebb10 · outbound

This paper cites SafeTraffic Copilot: adapting large language models for trustworthy traffic safety assessments and decision interventions,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives SafeTraffic Copilot: adapting large language models for trustworthy traffic safety assessments and decision interventions,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.269343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b71f581-a38b-4a7d-97dc-0e03ae761876 · outbound

This paper cites Injury severity on traffic crashes: A text mining with an interpretable machine-learning approach,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Injury severity on traffic crashes: A text mining with an interpretable machine-learning approach,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.273933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1ce4cd4-cc62-45dd-9c5a-8a8df4121ff0 · outbound

This paper cites Topic models from crash narrative reports of motorcycle crash causation study,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Topic models from crash narrative reports of motorcycle crash causation study,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.278290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03838482-e428-429d-8939-045e64a23b48 · outbound

This paper cites Industrial benchmarking of LLMs: Assessing hallucination in traffic incident scenarios with a novel spatio-temporal dataset,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Industrial benchmarking of LLMs: Assessing hallucination in traffic incident scenarios with a novel spatio-temporal dataset,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.282381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b634e3a3-1c52-4502-a8e1-c223fa81f0fd · outbound

This paper cites Identifying the causes of road traffic collisions: Using police officers’ expertise to improve the reporting of contributory factors data,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Identifying the causes of road traffic collisions: Using police officers’ expertise to improve the reporting of contributory factors data,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.286674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9004847-7390-4e42-8e64-de426af6ad38 · outbound

This paper cites Large Language Models for Traffic and Transportation Research: Methodologies, State of the Art, and Future Opportunities.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Large Language Models for Traffic and Transportation Research: Methodologies, State of the Art, and Future Opportunities

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.290860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76237a1b-96f2-4588-b2dc-9dbd87b5f662 · outbound

This paper cites Characteristics and availability of fatal road-crash databases in 20 countries worldwide,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Characteristics and availability of fatal road-crash databases in 20 countries worldwide,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.295984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ebea129-0fcc-4663-8d29-94326b44fe80 · outbound

This paper cites Under-reporting of road traffic crash data in Ghana,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Under-reporting of road traffic crash data in Ghana,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.300421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d59a6a1f-2117-4b00-905b-f4e0dc81d212 · outbound

This paper cites Crash narrative classification: Identifying agricultural crashes using machine learning with curated keywords,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Crash narrative classification: Identifying agricultural crashes using machine learning with curated keywords,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.304349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68f26fac-ed29-44c3-8864-8837be95cc37 · outbound

This paper cites Identification of Factors Contributing to Traffic Crashes by Analysis of Text Narratives,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Identification of Factors Contributing to Traffic Crashes by Analysis of Text Narratives,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.308302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65668d8e-e1fc-4b9f-9716-ba2fa5fd91be · outbound

This paper cites Predicting person-level injury severity using crash narratives: A balanced approach with roadway classification and natural language process techniques.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Predicting person-level injury severity using crash narratives: A balanced approach with roadway classification and natural language process techniques

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.312119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5746f959-13e1-4b4e-9a48-ddc3c538e369 · outbound

This paper cites Mining the highway-rail grade crossing crash data: A text mining approach,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Mining the highway-rail grade crossing crash data: A text mining approach,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.316892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e324db9e-82a0-401d-817d-3fafb9ce0abd · outbound

This paper cites Exploring traffic crash narratives in jordan using text mining analytics,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Exploring traffic crash narratives in jordan using text mining analytics,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.320753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80fb50c3-87ee-4cd3-9116-93bcec07fb17 · outbound

This paper cites New insights into road accident analysis through the use of text mining methods,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives New insights into road accident analysis through the use of text mining methods,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.324785Z

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Unavailable: canonical work link unavailable.

Observation bfd1b7c2-fc85-4763-aecb-ff392e5ad931 · outbound

This paper cites Discovering latent themes in traffic fatal crash narratives using text mining analytics and network topology,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Discovering latent themes in traffic fatal crash narratives using text mining analytics and network topology,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.328630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fffa60c-8cd5-4409-b3bd-990a2af48220 · outbound

This paper cites Extracting information from narratives: An application to aviation safety reports,.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Extracting information from narratives: An application to aviation safety reports,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.332679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55baefff-f5af-45d2-85a3-2237d0bab51b · outbound

This paper cites Towards Reliable and Interpretable Traffic Crash Pattern Prediction and Safety Interventions Using Customized Large Language Models.

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives Towards Reliable and Interpretable Traffic Crash Pattern Prediction and Safety Interventions Using Customized Large Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T14:22:25.337039Z

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Pith citing papers

No inbound Pith citation observations are available.