Paper Citation Record · LEDGER

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data

As of 16 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:1908.06817.

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

pith.paper-citation-record.v1
1908.06817 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:38:19.484373Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

29 of 29 outbound references displayed

verified exact1
verified fuzzy26
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 18442071-5767-4e87-a779-f5aaf5d7f312 · outbound

This paper cites Computer methods and programs in biomedicine 146, 11-24 (2017).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Computer methods and programs in biomedicine 146, 11-24 (2017)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.683685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 85ff4b1f-c3ef-4b5d-abe1-be8977ff004e · outbound

This paper cites Bioinformatics 21, 631-643 (2005).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Bioinformatics 21, 631-643 (2005)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.656622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 229e7737-1d7c-4236-b95a-2d64f6f77c4a · outbound

This paper cites Computer methods and programs in biomedicine 113, 465-473 (2014).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Computer methods and programs in biomedicine 113, 465-473 (2014)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.618131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 179bdf88-4708-4220-b05b-48b3954410e5 · outbound

This paper cites The Journal of urology 195, 493-498 (2016).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data The Journal of urology 195, 493-498 (2016)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.588923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0bdd3d17-a2f1-4c59-870c-51d20f016717 · outbound

This paper cites Machine Learning 45, 5-32 (2001).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Machine Learning 45, 5-32 (2001)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.568431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 506667f7-10b6-4d2a-920f-2985249b2f65 · outbound

This paper cites CRC press (1984).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data CRC press (1984)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-14T12:38:19.259597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dded79cf-d027-412f-9a9f-49bceea0b7a1 · outbound

This paper cites Human molecular genetics 23, 5866-5878 (2014).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Human molecular genetics 23, 5866-5878 (2014)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.518618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f05b0679-a440-4963-9490-7a73eb6ea807 · outbound

This paper cites Nature genetics 45, 1113 (2013).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Nature genetics 45, 1113 (2013)

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.450622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bd3e33ac-d7af-496c-8d74-6e2e8228e274 · outbound

This paper cites Asian Pacific Journal of Cancer Prevention 17, 835-838 (2016).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Asian Pacific Journal of Cancer Prevention 17, 835-838 (2016)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.425588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e6793f1e-4228-4b75-81a8-d7f3a39742e3 · outbound

This paper cites Egyptian Informatics Journal 18, 151-159 (2017).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Egyptian Informatics Journal 18, 151-159 (2017)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.365947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3ca9ef55-9225-4a9d-b6b0-8479347ed1e9 · outbound

This paper cites BMC bioinformatics 7, 3 (2006).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data BMC bioinformatics 7, 3 (2006)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.321091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b3ba096d-273c-474a-b0d5-1e40ac72aa83 · outbound

This paper cites Computational Biology and Chemistry 28, 235-243 (2004).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Computational Biology and Chemistry 28, 235-243 (2004)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.297521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a82402b6-9738-4e04-9a36-2b25b7fabd8e · outbound

This paper cites R: A language and environment for statistical computing.

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data R: A language and environment for statistical computing

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.253883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ba50139e-99b1-4a95-aa96-81aa20f5393f · outbound

This paper cites Computers in biology and medicine 81, 139-147 (2017).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Computers in biology and medicine 81, 139-147 (2017)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.187987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5cc76363-5bf7-4bc0-8bd6-fac782223789 · outbound

This paper cites rFerns: An Implementation of the Random Ferns Method for General-Purpose Machine Learning.

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data rFerns: An Implementation of the Random Ferns Method for General-Purpose Machine Learning

Reference 15

Resolution: metadata mismatch; local_arxiv, observed 2026-08-14T12:38:19.707560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8e63caeb-0f38-4663-a10f-6bc8cb23843a · outbound

This paper cites -S., He, X.

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data -S., He, X

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.156415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7e1ae21c-811a-45f4-80ab-deea4430921b · outbound

This paper cites Machine learning 63, 3-42 (2006).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Machine learning 63, 3-42 (2006)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.114142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5b49b2c4-ce1a-4221-9379-37e5bff20be9 · outbound

This paper cites Pattern Recognition 45, 3141-3153 (2012).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Pattern Recognition 45, 3141-3153 (2012)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.079165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 25f98c0a-e7ef-49aa-9203-bae147954950 · outbound

This paper cites , Wang, Z., Ding, W.: Support vector machine classifier for prediction of the metastasis of colorectal cancer.

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data , Wang, Z., Ding, W.: Support vector machine classifier for prediction of the metastasis of colorectal cancer

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.048774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fef5c21c-b71d-4556-90e7-dfe06198ea4b · outbound

This paper cites PloS one 12, e0189875 (2017).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data PloS one 12, e0189875 (2017)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:20.016905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 42e970f3-cee4-4d07-ac19-a747752bd8cb · outbound

This paper cites Optics & Laser Technology 102, 233-239 (2018).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Optics & Laser Technology 102, 233-239 (2018)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:19.980794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8e510481-3c91-4876-ac78-9ff826dc2ce8 · outbound

This paper cites Scientific reports 4, 4184 (2014).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Scientific reports 4, 4184 (2014)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:19.947352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 689aeb8d-1485-47b9-bc04-919159f4e6d6 · outbound

This paper cites Springer series in statistics Springer, Berlin (2001).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Springer series in statistics Springer, Berlin (2001)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:19.919345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 689aaf74-62d5-4321-b07a-1d814b50a0c8 · outbound

This paper cites IEEE Transactions on Information Theory 13, 21-27 (1967).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data IEEE Transactions on Information Theory 13, 21-27 (1967)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:19.880242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation dc3db88d-b52b-4398-a125-51ad696726eb · outbound

This paper cites Cl inical Cancer Research (2018).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Cl inical Cancer Research (2018)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:19.841587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 35428d48-bc67-4b34-94cd-e4f6d589e396 · outbound

This paper cites Cancer research canres.

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Cancer research canres

Reference 26

Resolution: verified exact; raw_fallback, observed 2026-08-14T12:38:19.646906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f4e6890a-0002-4aa3-aef3-b4ce176dd556 · outbound

This paper cites British journal of haematology (2018).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data British journal of haematology (2018)

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:19.800737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6cdd8c9d-3e4f-4fde-a6de-a8036dff29da · outbound

This paper cites PloS one 9, e85110 (2014).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data PloS one 9, e85110 (2014)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:19.769293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 331dd6c1-626d-4474-bc35-220a273a15d8 · outbound

This paper cites Nature 499, 214 (2013).

The efficacy of various machine learning models for multi-class classification of RNA-seq expression data Nature 499, 214 (2013)

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:38:19.734894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.