Paper Citation Record · LEDGER

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts

As of 20 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2505.21324.

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

pith.paper-citation-record.v1
2505.21324 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:35:52.211218Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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 exact7
verified fuzzy3
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bffa37f9-850b-41f9-9f54-bbd0a7fb46d7 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:57.337985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation beb74ad9-dd56-4994-997d-cafe3e7d05f6 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 2

Resolution: verified exact; doi, observed 2026-08-07T13:35:53.862553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 929bce7b-ccf5-41b6-a3d5-4b322b1465e1 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T13:35:49.187860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bd93c5a-9757-4d1c-81f0-3a119f4c523f · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 4

Resolution: verified exact; doi, observed 2026-08-07T13:35:53.646615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1f9a69cb-301a-469b-a859-8aaa0877b3b0 · outbound

This paper cites Language Models are Few-Shot Learners.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Language Models are Few-Shot Learners

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T13:35:49.374043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29034979-5b59-49e1-b892-fbbc3e077ffb · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:57.018000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f37df7e8-de84-4c13-be41-4499952221b9 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 7

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T13:35:54.359156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7ccbff2a-19c1-4686-832a-41c0144130fb · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:56.832840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 77d48d5d-86e5-404d-b805-b93ab6c3fa0a · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:56.615142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6461fe7b-9607-4430-965a-8f08ffef464c · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:56.434905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 45c36fef-a9d2-440e-bc16-52945009b337 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:56.255758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 720acf51-810e-43e0-b8fa-63384979fdbc · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:56.076162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c5c1e82c-5d33-4cb6-9b73-5157daeb63bb · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 13

Resolution: verified exact; doi, observed 2026-08-07T13:35:53.444273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 726e5283-d197-4ad2-9194-2cd23206cbab · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 14

Resolution: verified exact; doi, observed 2026-08-07T13:35:53.235506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 44fa6184-57aa-4141-817a-aa9e6494496c · outbound

This paper cites Detecting a Proxy for Potential Comorbid ADHD in People Reporting Anxiety Symptoms from Social Media Data.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Detecting a Proxy for Potential Comorbid ADHD in People Reporting Anxiety Symptoms from Social Media Data

Reference 15

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T13:35:54.068323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 989df8e6-2763-412a-a2ae-eb49f545b967 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:55.913709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 01133ed1-cc3b-4d23-b0fe-b694fba2c0bc · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T13:35:50.843833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 341f9aa1-59ce-4676-bafc-d09aab1b9c24 · outbound

This paper cites Nguyen, Yuta Y.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Nguyen, Yuta Y

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:35:55.748192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f3513d89-e790-4d73-9660-5f1b9da2da0b · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:55.502207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5ffc3c7c-4fca-44c5-89cd-cd8236e45c68 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T13:35:51.601330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f2e7ee5-b5b6-4296-8d23-6cb33519c6d3 · outbound

This paper cites Pulini, Wesley T.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Pulini, Wesley T

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:35:55.254444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 74b7f85c-4dc1-45ff-8064-7652ece5631a · outbound

This paper cites Dey, and Dakuo Wang.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Dey, and Dakuo Wang

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T13:35:51.823756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d438844-edd5-49d4-98ef-d87c6e112d3c · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:54.838008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d869504f-bb4c-4364-8f36-a29c33e7cd81 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:35:54.550521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2ba75c81-c5a5-457f-852c-4b22217f3828 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T13:35:51.709562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1aca7220-bfed-4577-afef-2364d851f751 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 120

Resolution: verified exact; doi, observed 2026-08-07T13:35:52.679871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6fd5dfe0-a2a0-468c-a978-b97add9da839 · outbound

This paper cites an unresolved cited work.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Unresolved cited work

Reference 957

Resolution: verified exact; doi, observed 2026-08-07T13:35:52.951121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0e2cfcf1-1154-43d7-8611-82b6301d34e9 · outbound

This paper cites Biological Psychiatry: Cognitive Neuroscience and Neuroimaging4, 2 (2019), 108–.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts Biological Psychiatry: Cognitive Neuroscience and Neuroimaging4, 2 (2019), 108–

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:35:55.041196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9560b367-d04c-4cce-adc2-f89f794f2575 · outbound

This paper cites doi:10.1101/2023.12.21.23300380 arXiv:https://www.medrxiv.org/content/early/2023/12/24/2023.12.21.23300380.full.pdf.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts doi:10.1101/2023.12.21.23300380 arXiv:https://www.medrxiv.org/content/early/2023/12/24/2023.12.21.23300380.full.pdf

Reference 2023

Resolution: verified exact; doi, observed 2026-08-07T13:35:52.467696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.