Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T16:37:34.845464Z
Paper Citation Record · LEDGER
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy
As of 9 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2502.06150.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
15 of 15 outbound references displayed
- verified exact0
- verified fuzzy6
- unresolved9
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 2c470cc6-ddac-4ac7-910b-ae9f23ac1873 · outbound
This paper cites A contrastive topic-aware attentive framework with label encodings for post-disaster resource classification,.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy A contrastive topic-aware attentive framework with label encodings for post-disaster resource classification,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:37:35.217493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7b58674c-8b74-4f71-ae99-5ccca02e4eb6 · outbound
This paper cites Crowdsourcing for machine learning in public health surveillance: Lessons learned from amazon mechanical turk,.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy Crowdsourcing for machine learning in public health surveillance: Lessons learned from amazon mechanical turk,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:37:35.201814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 880a328b-909c-4d97-baa1-7b9904b5f8f7 · outbound
This paper cites Who broke amazon mechanical turk? an analysis of crowdsourcing data quality over time,.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy Who broke amazon mechanical turk? an analysis of crowdsourcing data quality over time,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:37:35.185970Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation c195c93e-b984-4522-9adf-80198bd720ba · outbound
This paper cites The Perils of Using Mechanical Turk to Evaluate Open-Ended Text Generation.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy The Perils of Using Mechanical Turk to Evaluate Open-Ended Text Generation
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:37:34.791518Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 59598503-96b1-448d-8f61-58a2fef334e6 · outbound
This paper cites Language Models are Few-Shot Learners.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy Language Models are Few-Shot Learners
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:37:34.797008Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9f13c495-0800-4826-836c-f907e2126797 · outbound
This paper cites Language models are unsupervised multitask learners,.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy Language models are unsupervised multitask learners,
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:37:34.802150Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5bf12a7e-acd4-4d3a-98de-c3f79ed19a96 · outbound
This paper cites an unresolved cited work.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T16:37:35.160792Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 980645f7-5499-479a-af4d-577f75dc5645 · outbound
This paper cites ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:37:34.817466Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7557e61-f8f7-4b11-b907-8aab849a5706 · outbound
This paper cites Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Tasks.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Tasks
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:37:34.822700Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7aa6a268-af44-43ad-a4a7-e2a7d92bb99b · outbound
This paper cites Chatgpt outperforms crowd workers for text-annotation tasks,.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy Chatgpt outperforms crowd workers for text-annotation tasks,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:37:35.145725Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation dbc09b0e-36c3-42c0-98ee-6e9b89620671 · outbound
This paper cites Physical activity, sedentary behavior, and sleep on twitter: Multicountry and fully labeled public data set for digital public health surveillance research,.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy Physical activity, sedentary behavior, and sleep on twitter: Multicountry and fully labeled public data set for digital public health surveillance research,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:37:35.130465Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 703aec85-13fa-45d5-9c80-2fb542c58d63 · outbound
This paper cites [Online].
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:37:35.113988Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 529ce6db-b003-4449-9183-bc5f6f0d6699 · outbound
This paper cites Evaluation of openai o1: Opportuni- ties and challenges of agi,.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy Evaluation of openai o1: Opportuni- ties and challenges of agi,
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:37:34.841175Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation df1d08ca-e9ca-4dca-8949-8a5ce3efe832 · outbound
This paper cites LoRA: Low-Rank Adaptation of Large Language Models.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy LoRA: Low-Rank Adaptation of Large Language Models
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:37:34.845464Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 91539db9-b48d-40c4-8e3e-43fc1abfe967 · outbound
This paper cites Is ChatGPT a General-Purpose Natural Language Processing Task Solver?.
Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy Is ChatGPT a General-Purpose Natural Language Processing Task Solver?
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:37:34.812533Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.