Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T11:39:13.935167Z
Paper Citation Record · LEDGER
Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper
As of 16 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:1908.08610.
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 2026-08-16T06:30:59.297886+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
7 of 7 outbound references displayed
- verified exact0
- verified fuzzy6
- unresolved1
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f66b1f15-7327-4179-b053-0229d1edb9a8 · outbound
This paper cites Systematic reviews: rationale for systematic reviews.
Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper Systematic reviews: rationale for systematic reviews
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T11:39:14.027354Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1bbebff6-1717-4e55-9f39-1411acfa6576 · outbound
This paper cites Cochrane handbook for systematic reviews of interventions.
Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper Cochrane handbook for systematic reviews of interventions
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T11:39:14.017244Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 58dae8b6-84a8-4642-bc48-1fece56d67ec · outbound
This paper cites Foundations of machine learning.
Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper Foundations of machine learning
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T11:39:14.007038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation af8753ae-26c4-4d44-95d9-234f7636f6eb · outbound
This paper cites O'Reilly Media, Inc.
Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper O'Reilly Media, Inc
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T11:39:13.922848Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 38a0c21a-6ce3-400b-8471-afc047a7e071 · outbound
This paper cites Mining of massive datasets.
Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper Mining of massive datasets
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T11:39:13.988055Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation efb9f57a-f960-4dd0-9971-f808d346b59c · outbound
This paper cites Scikit-learn: Machine learning in Python.
Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper Scikit-learn: Machine learning in Python
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T11:39:13.978237Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1b4af073-cfe3-4510-a61e-f0c6cf129152 · outbound
This paper cites Class imbalance learning methods for support vector machines.
Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper Class imbalance learning methods for support vector machines
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T11:39:13.967464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.