Paper Citation Record · LEDGER

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale

As of 23 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 2 inbound Pith citation observations for arXiv:2502.00943.

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

pith.paper-citation-record.v1
2502.00943 v2

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:15:21.562885Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:15:11.338949Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T05:56:40.409151Z

Reference resolution

26 of 26 outbound references displayed

verified exact1
verified fuzzy17
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d57e0a80-c9b3-4d23-b295-c3a0794e3412 · outbound

This paper cites write newline.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-09T17:15:21.484468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38f20619-4f44-4d6f-88a2-38c577fc9d78 · outbound

This paper cites an unresolved cited work.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-09T17:15:21.943168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 21a1cb0c-2822-4385-9f88-db6d43ed64d2 · outbound

This paper cites Classifying cancer pathology reports with hierarchical self-attention networks.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Classifying cancer pathology reports with hierarchical self-attention networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.934308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 118e4f59-4b39-444e-8ab1-f558d809a80c · outbound

This paper cites Limitations of transformers on clinical text classification.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Limitations of transformers on clinical text classification

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.924050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6e877812-2a5b-4b63-b9d0-c0cea3639edf · outbound

This paper cites Automating access to real-world evidence.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Automating access to real-world evidence

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.912996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fb33ee54-efde-4623-a9f2-bb3f5152aa65 · outbound

This paper cites Llms accelerate annotation for medical information extraction, 2023.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Llms accelerate annotation for medical information extraction, 2023

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.901087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 10d09e22-f760-476f-a2f6-bf0edcccd683 · outbound

This paper cites Trialscope: A unifying causal framework for scaling real-world evidence generation with biomedical language models.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Trialscope: A unifying causal framework for scaling real-world evidence generation with biomedical language models

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.890037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b94db642-7321-4cb9-bd72-b2f5614683c2 · outbound

This paper cites Improving large language models for clinical named entity recognition via prompt engineering.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Improving large language models for clinical named entity recognition via prompt engineering

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T17:15:21.510160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74265437-e3bb-4d97-8842-26c2e9bf1e29 · outbound

This paper cites Generalizable and automated classification of tnm stage from pathology reports with external validation.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Generalizable and automated classification of tnm stage from pathology reports with external validation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.880707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 34aed266-a40e-4429-b590-27603146413b · outbound

This paper cites Benefits, limits, and risks of gpt-4 as an ai chatbot for medicine.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Benefits, limits, and risks of gpt-4 as an ai chatbot for medicine

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.872049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0c643ae7-f143-430b-91d5-97f03af787a1 · outbound

This paper cites Lost in the middle: How language models use long contexts.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Lost in the middle: How language models use long contexts

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T17:15:21.519804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa9aedf9-964c-45d2-a957-dfc1d1894399 · outbound

This paper cites Cancer registrar workload and staffing study: Guidelines for hospital cancer registry programs.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Cancer registrar workload and staffing study: Guidelines for hospital cancer registry programs

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.858778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f7b5ff9e-eaa5-480e-b164-ab8b589f0b5e · outbound

This paper cites GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T17:15:21.525504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67f4759e-c501-4f87-bbc0-67f2b9a641af · outbound

This paper cites Salary considerations for cancer registrars: 2022.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Salary considerations for cancer registrars: 2022

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.851511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2da72bd8-18ee-4089-89c5-166a5623df38 · outbound

This paper cites Revised recist guideline version 1.1: what oncologists want to know and what radiologists need to know.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Revised recist guideline version 1.1: what oncologists want to know and what radiologists need to know

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.843145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 63439647-7d7c-4a68-9ad1-5432f327fa65 · outbound

This paper cites Can generalist foundation models outcompete special-purpose tuning? case study in medicine.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Can generalist foundation models outcompete special-purpose tuning? case study in medicine

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.835063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c5376a3e-3732-4f14-8112-1b72abcf65a1 · outbound

This paper cites Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.825778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 79fbbca7-43b5-4f38-989c-7dd911a8967f · outbound

This paper cites Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision.

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.815962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5cfa277a-f167-4a61-b11d-69e4e1c8614b · outbound

This paper cites Tnm classification.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Tnm classification

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.806742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4d1e2781-2d94-49ec-b978-73f31fe9204d · outbound

This paper cites Opportunities and challenges in using real-world data for health care.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Opportunities and challenges in using real-world data for health care

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.797308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3ce61f05-787e-4ca4-ae9c-ea951a399248 · outbound

This paper cites Estimating redundancy in clinical text.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Estimating redundancy in clinical text

Reference 21

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T17:15:21.751841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cdc0d003-06a1-4cea-b796-141e068a66c5 · outbound

This paper cites Scaling clinical trial matching using large language models: A case study in oncology, 2023.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Scaling clinical trial matching using large language models: A case study in oncology, 2023

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.788100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 22c448bc-494d-4377-b99a-4f5e4a40a18f · outbound

This paper cites Universalner: Targeted distillation from large language models for open named entity recognition, 2024.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Universalner: Targeted distillation from large language models for open named entity recognition, 2024

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:15:21.777550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fae3f2c5-6ec8-4355-b027-6b3f5a83f981 · outbound

This paper cites @esa (Ref.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale @esa (Ref

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T17:15:21.557199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca967e75-756f-4a43-96dd-895626f62b2b · outbound

This paper cites an unresolved cited work.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T17:15:21.560148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da4d2efa-599e-4d89-b630-c4fdfbc2a6b6 · outbound

This paper cites performance status measurement type.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale performance status measurement type

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-09T17:15:21.562885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 71f06a7b-766f-4139-80f5-ef3a15100d30 · inbound

Predicting Early-Onset Colorectal Cancer with Large Language Models cites this paper.

Predicting Early-Onset Colorectal Cancer with Large Language Models Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T04:15:11.338949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 170f13b5-ade7-48ca-8147-aaa399875c84 · inbound

MeDxAgent: Multi-Agent Consultation for Interactive Medical Diagnosis cites this paper.

MeDxAgent: Multi-Agent Consultation for Interactive Medical Diagnosis Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:40.411060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.