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Paper Citation Record · LEDGER

Natural Language Processing Psychometrics

As of 11 August 2026, this Paper Citation Record lists 92 of 92 outbound references and 0 inbound Pith citation observations for arXiv:2608.07316.

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

pith.paper-citation-record.v1
2608.07316 v1

Coverage vector

measured 92 of 92 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T10:28:41.613505Z

measured 92 of 92 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

92 of 92 outbound references displayed

  • verified exact2
  • verified fuzzy49
  • unresolved40
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b1e2655d-4c2b-46e5-bd06-44415487eec4 · outbound

This paper cites an unresolved cited work.

Natural Language Processing Psychometrics Unresolved cited work

Reference 1

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no resolver link, observed 2026-08-10T10:28:39.983288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 745c874e-c794-42d5-9f15-e4479ad66d4c · outbound

This paper cites Self-efficacy and locus of control when facing listening challenges: Validation of the listening challenges attitude scale (licas).

Natural Language Processing Psychometrics Self-efficacy and locus of control when facing listening challenges: Validation of the listening challenges attitude scale (licas)

Reference 2

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no resolver link, observed 2026-08-10T10:28:39.987594Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T10:28:39.987594Z digest=sha256:d37a5c898ed5f35d02c219ca5f7e4103ab6cc0d766bf2142ecc43f2167cc9fbb

Observation de169a24-1582-4adc-baa0-bd508c75b24d · outbound

This paper cites Exploratory factor analysis: Current use, methodological developments and recommendations for good practice.Current psychology, 40(7):3510–3521, 2021.

Natural Language Processing Psychometrics Exploratory factor analysis: Current use, methodological developments and recommendations for good practice.Current psychology, 40(7):3510–3521, 2021

Reference 3

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no resolver link, observed 2026-08-10T10:28:39.991313Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T10:28:39.991313Z digest=sha256:a3cdfef81b1ac8b71fcf35c372c9c1f8243936957c1b9721fdb4e26c872a7c2a

Observation 46b8bff0-72b5-49dc-9e1a-5ff7c4d4f916 · outbound

This paper cites Dasentimental: Detecting depression, anxiety, and stress in texts via emotional recall, cognitive networks, and machine learning.Big data and cognitive computing, 5(4):77, 2021.

Natural Language Processing Psychometrics Dasentimental: Detecting depression, anxiety, and stress in texts via emotional recall, cognitive networks, and machine learning.Big data and cognitive computing, 5(4):77, 2021

Reference 4

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no resolver link, observed 2026-08-10T10:28:39.995346Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T10:28:39.995346Z digest=sha256:ab644387e42f7cdcea644356e48fc2ea3edc6bf555b08a0f0cdd53f9ef7457b6

Observation d5ac2b1e-3725-4979-8c95-318987b7e3d5 · outbound

This paper cites LLMs can persuade only psychologically susceptible humans on societal issues, via trust in AI and emotional appeals, amid logical fallacies.

Natural Language Processing Psychometrics LLMs can persuade only psychologically susceptible humans on societal issues, via trust in AI and emotional appeals, amid logical fallacies

Reference 5

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no resolver link, observed 2026-08-10T10:28:39.999382Z

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source=pdf_text observed=2026-08-10T10:28:39.999382Z digest=sha256:d3f06884cee9fc5bd45e0c1e55b76a8e41872217b3c7226f89e0eb9f9492ec43

Observation 077a0456-a707-4b91-a3ba-48a4971e7801 · outbound

This paper cites Examining linguistic differences in electronic health records for diverse patients with diabetes: natural language processing analysis.JMIR Medical Informatics, 12(1):e50428, 2024.

Natural Language Processing Psychometrics Examining linguistic differences in electronic health records for diverse patients with diabetes: natural language processing analysis.JMIR Medical Informatics, 12(1):e50428, 2024

Reference 6

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no resolver link, observed 2026-08-10T10:28:40.003838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:40.003838Z digest=sha256:3915a3ed9263c682b62763fd4c4af5bf3fb74fb8032e85959ba3f1786ad4b3a3

Observation 89e3c163-096c-46be-bd19-332e82ee5719 · outbound

This paper cites Language is primarily a tool for communication rather than thought.Nature, 630(8017):575–586, 2024.

Natural Language Processing Psychometrics Language is primarily a tool for communication rather than thought.Nature, 630(8017):575–586, 2024

Reference 7

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no resolver link, observed 2026-08-10T10:28:40.007891Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T10:28:40.007891Z digest=sha256:9649df5f33a32ada461c73be2ecabb717c934eaf63b45c7b748d81600931f656

Observation 16f94765-ac0a-4a1e-8ca1-0cef0e55e18f · outbound

This paper cites John Wiley & Sons, 2012.

Natural Language Processing Psychometrics John Wiley & Sons, 2012

Reference 8

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no resolver link, observed 2026-08-10T10:28:40.052575Z

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source=pdf_text observed=2026-08-10T10:28:40.052575Z digest=sha256:d1a25a3db90bfdf94e3c5f92641e14f8123c8279851f86d39e219534138390cb

Observation 88ddbb29-0316-48b9-a1bf-b5286802f983 · outbound

This paper cites Deep lexical hypothesis: Identifying personality structure in natural language.Journal of Personality and Social Psychology, 125(1):173, 2023.

Natural Language Processing Psychometrics Deep lexical hypothesis: Identifying personality structure in natural language.Journal of Personality and Social Psychology, 125(1):173, 2023

Reference 9

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no resolver link, observed 2026-08-10T10:28:40.110876Z

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source=pdf_text observed=2026-08-10T10:28:40.110876Z digest=sha256:158701018070c7a59039543c42d8bdbe13861f8ba9314a067f432fca1e89d7c4

Observation ded9a208-4df7-4188-a4b7-2f97ac9102f6 · outbound

This paper cites Emoatlas: An emotional network analyzer of texts that merges psychological lexicons, artificial intelligence, and network science.Behavior Research Methods, 57(2):77, 2025.

Natural Language Processing Psychometrics Emoatlas: An emotional network analyzer of texts that merges psychological lexicons, artificial intelligence, and network science.Behavior Research Methods, 57(2):77, 2025

Reference 10

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no resolver link, observed 2026-08-10T10:28:40.144611Z

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source=pdf_text observed=2026-08-10T10:28:40.144611Z digest=sha256:4ad31a087b54ac71463f0fe0fc93af45e3bcade073e43171a4fbf8d82138ca9f

Observation 6613b261-354f-4214-9801-affb04556e83 · outbound

This paper cites Using complex networks to understand the mental lexicon.

Natural Language Processing Psychometrics Using complex networks to understand the mental lexicon

Reference 11

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no resolver link, observed 2026-08-10T10:28:40.245992Z

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source=pdf_text observed=2026-08-10T10:28:40.245992Z digest=sha256:714fabbf2d11dbdd59bc27f6827a6101f75c3d5366b073df94212724a57e15c9

Observation f3b2f4fe-67ea-4414-b797-ab2dcf1f0ca5 · outbound

This paper cites Structure and flexibility: Inves- tigating the relation between the structure of the mental lexicon, fluid intelligence, and creative achievement.

Natural Language Processing Psychometrics Structure and flexibility: Inves- tigating the relation between the structure of the mental lexicon, fluid intelligence, and creative achievement

Reference 12

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no resolver link, observed 2026-08-10T10:28:40.301944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:40.301944Z digest=sha256:f34438d7b8bad644c62e40eefbcc3e6ad4606e84cf18e22370520a0fff3c0c62

Observation 19aeb13c-ecf8-4c5b-943a-e7522a81f37e · outbound

This paper cites Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges.Psychonomic Bulletin & Review, 31(5):1981–2004, 2024.

Natural Language Processing Psychometrics Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges.Psychonomic Bulletin & Review, 31(5):1981–2004, 2024

Reference 13

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no resolver link, observed 2026-08-10T10:28:40.349388Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T10:28:40.349388Z digest=sha256:6fb2953582ae1da9e199475122bcc22c7486af0d465ea78d28c1cbc4974d33b7

Observation 6c9ee9ee-f456-49a3-b505-e07068253408 · outbound

This paper cites In an absolute state: Elevated use of absolutist words is a marker specific to anxiety, depression, and suicidal ideation.Clinical psychological science, 6(4):529–542, 2018.

Natural Language Processing Psychometrics In an absolute state: Elevated use of absolutist words is a marker specific to anxiety, depression, and suicidal ideation.Clinical psychological science, 6(4):529–542, 2018

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-10T10:28:44.363328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 6e979e0e-1a35-40db-806b-850b9eab5b87 · outbound

This paper cites How do users of a mental health app conceptualise digital therapeutic alliance? a qualitative study using the framework approach.

Natural Language Processing Psychometrics How do users of a mental health app conceptualise digital therapeutic alliance? a qualitative study using the framework approach

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-10T10:28:44.351986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 411fa2f5-6def-4ee7-964d-87681d7c24c9 · outbound

This paper cites Detecting and measuring depression on social media using a machine learning approach: systematic review.JMIR Mental Health, 9(3): e27244, 2022.

Natural Language Processing Psychometrics Detecting and measuring depression on social media using a machine learning approach: systematic review.JMIR Mental Health, 9(3): e27244, 2022

Reference 16

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raw_fallback, observed 2026-08-10T10:28:44.338797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 3bb1bbf1-2acd-4bc5-9541-05907a09b50c · outbound

This paper cites Predicting depression via social media.

Natural Language Processing Psychometrics Predicting depression via social media

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation b056d8d3-b271-4a7f-a471-e031b8fbf63c · outbound

This paper cites Digital shadows in mental health map how llms simulate depression, anxiety, and stress through language and psychometrics.PsyArXiv,.

Natural Language Processing Psychometrics Digital shadows in mental health map how llms simulate depression, anxiety, and stress through language and psychometrics.PsyArXiv,

Reference 18

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 2431d8f9-d7b7-4d8c-bb6f-dd5623e4459e · outbound

This paper cites Harvard University, 2024.

Natural Language Processing Psychometrics Harvard University, 2024

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 39780863-611b-48a5-8fb3-1cfaa77e8dd1 · outbound

This paper cites Text psychometrics: Assessing psychological constructs in text using natural language processing, 2026.

Natural Language Processing Psychometrics Text psychometrics: Assessing psychological constructs in text using natural language processing, 2026

Reference 20

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raw_fallback, observed 2026-08-10T10:28:44.138565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation f81dee48-e414-4b99-a789-66eada5bae9e · outbound

This paper cites an unresolved cited work.

Natural Language Processing Psychometrics Unresolved cited work

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 7c6fa032-e694-41e5-abe3-5d1b4aa0a68f · outbound

This paper cites The phq-9: validity of a brief depression severity measure.Journal of general internal medicine, 16(9):606–613, 2001.

Natural Language Processing Psychometrics The phq-9: validity of a brief depression severity measure.Journal of general internal medicine, 16(9):606–613, 2001

Reference 22

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raw_fallback, observed 2026-08-10T10:28:43.935946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:40.669938Z digest=sha256:44a3c329a4ac5a3e1e24dd9585fa4a0df5e8ca8f1e4e14395e3dbb815f386160

Observation 7557b040-d2f3-4de6-9340-2e4ce37988c1 · outbound

This paper cites Mapping how LLMs debate societal issues when shadowing human personality traits, sociodemographics and social media behavior.

Natural Language Processing Psychometrics Mapping how LLMs debate societal issues when shadowing human personality traits, sociodemographics and social media behavior

Reference 23

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no resolver link, observed 2026-08-10T10:28:40.674371Z

Source-reported events for the cited work

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Observation 0b1f849f-3da9-4be9-93cd-6449c15ee848 · outbound

This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

Natural Language Processing Psychometrics Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 24

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no resolver link, observed 2026-08-10T10:28:40.679110Z

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Observation 3661d8af-ed78-4667-bc52-02981617fb83 · outbound

This paper cites an unresolved cited work.

Natural Language Processing Psychometrics Unresolved cited work

Reference 25

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unresolved
raw_fallback, observed 2026-08-10T10:28:43.924579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 6b91d091-394e-499a-87e6-1f173e29c6f6 · outbound

This paper cites Escaping the jingle-jangle jungle: Increasing conceptual clarity in psychology using large language models.Current Directions in Psychological Science, 35(2):59–65, 2026.

Natural Language Processing Psychometrics Escaping the jingle-jangle jungle: Increasing conceptual clarity in psychology using large language models.Current Directions in Psychological Science, 35(2):59–65, 2026

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 91ba97af-fd76-441c-8801-045a6af6f1cf · outbound

This paper cites Lost in the middle: How language models use long contexts.Transactions of the Association for Computational Linguistics, 12:157–173, 2024.

Natural Language Processing Psychometrics Lost in the middle: How language models use long contexts.Transactions of the Association for Computational Linguistics, 12:157–173, 2024

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bc40b7b3-e75f-4a8b-9b4b-eadadc14df87 · outbound

This paper cites Large language models accurately identify decision reasons in verbal reports.Proceedings of the National Academy of Sciences, 123(27):e2526798123, 2026.

Natural Language Processing Psychometrics Large language models accurately identify decision reasons in verbal reports.Proceedings of the National Academy of Sciences, 123(27):e2526798123, 2026

Reference 28

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raw_fallback, observed 2026-08-10T10:28:43.893799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 0195748e-56b6-457f-8537-4164d33fc240 · outbound

This paper cites Evaluating llms for synthetic personas generation: A comparative analysis of personality representation and censorship effects.

Natural Language Processing Psychometrics Evaluating llms for synthetic personas generation: A comparative analysis of personality representation and censorship effects

Reference 29

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raw_fallback, observed 2026-08-10T10:28:43.882395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation f2fd1f7e-038b-42bd-91e4-81fff6675ded · outbound

This paper cites Quantifying the Persona Effect in LLM Simulations.

Natural Language Processing Psychometrics Quantifying the Persona Effect in LLM Simulations

Reference 30

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no resolver link, observed 2026-08-10T10:28:40.702619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bffd59bc-6fc8-44e6-a78a-210354e90ac3 · outbound

This paper cites Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable.

Natural Language Processing Psychometrics Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable

Reference 31

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no resolver link, observed 2026-08-10T10:28:40.706927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:40.706927Z digest=sha256:fc75e000953a02c484d6ffd9ac8a4049136ddaa8f7252a25f0b4cda38d882d18

Observation 1c41d8a0-da19-4014-91a7-f20a5ce69f8d · outbound

This paper cites Large language models that replace human participants can harmfully misportray and flatten identity groups.Nature Machine Intelligence, 7(3):400–411, 2025.

Natural Language Processing Psychometrics Large language models that replace human participants can harmfully misportray and flatten identity groups.Nature Machine Intelligence, 7(3):400–411, 2025

Reference 32

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raw_fallback, observed 2026-08-10T10:28:43.870155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 27c972a1-0342-48a9-ab19-21c4e8091165 · outbound

This paper cites Large language models are homogeneously creative.PNAS nexus, 5(3): pgag042, 2026.

Natural Language Processing Psychometrics Large language models are homogeneously creative.PNAS nexus, 5(3): pgag042, 2026

Reference 33

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raw_fallback, observed 2026-08-10T10:28:43.856344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 33f47695-95a6-4954-bd77-4390877bf431 · outbound

This paper cites Math Education Digital Shadows for Investigating Learning with GenAI: Mathematics Performance, Anxiety, and Confidence in LLMs.

Natural Language Processing Psychometrics Math Education Digital Shadows for Investigating Learning with GenAI: Mathematics Performance, Anxiety, and Confidence in LLMs

Reference 34

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local_arxiv, observed 2026-08-10T10:28:41.980560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:40.718671Z digest=sha256:d26d3fda18bb77db57e33f68e592c4986a9e6764ef9c188872df810a2bf37ca0

Observation d692acfa-3335-462c-88dc-b7cc69419ebd · outbound

This paper cites an unresolved cited work.

Natural Language Processing Psychometrics Unresolved cited work

Reference 35

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raw_fallback, observed 2026-08-10T10:28:43.844790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:40.722974Z digest=sha256:c1a602971000f942893124cd101f37f79d38af2eb17ccef4a2df67164fdbd05e

Observation 1a04c9dc-41ab-4c93-a4d9-e615e8985bd4 · outbound

This paper cites an unresolved cited work.

Natural Language Processing Psychometrics Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-10T10:28:43.834051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:40.726854Z digest=sha256:c65b5a93357bd5c3c41bb6b704d00b0e7654b58c51d837e02bde0daa8326ace1

Observation 857aa70d-d18a-4234-9f86-750102770959 · outbound

This paper cites A diagnostic meta-analysis of the patient health questionnaire- 9 (phq-9) algorithm scoring method as a screen for depression.General hospital psychiatry, 37(1):67–75, 2015.

Natural Language Processing Psychometrics A diagnostic meta-analysis of the patient health questionnaire- 9 (phq-9) algorithm scoring method as a screen for depression.General hospital psychiatry, 37(1):67–75, 2015

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.776578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:40.730776Z digest=sha256:e81f6c0cb69830cb2fe104929aba2f9a45e62f38f5547244c34cd2cafadacb6e

Observation 81875dbc-cac9-408b-84c6-ac40135d7626 · outbound

This paper cites Using network science to analyze concept maps of psychology undergraduates.Applied Cognitive Psychology, 33(4):662–668, 2019.

Natural Language Processing Psychometrics Using network science to analyze concept maps of psychology undergraduates.Applied Cognitive Psychology, 33(4):662–668, 2019

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.571108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:40.734200Z digest=sha256:e848d34cb895bf5d1fe5b7a1eecec0e405ffce75b9ff0a2b8585bf0a5c838f9f

Observation be89c6d0-da48-4f50-9794-9aaa9e43e25a · outbound

This paper cites Cognitive networks for knowledge modeling: A gentle introduction for data-and cognitive scientists.Wiley Interdisciplinary Reviews: Cognitive Science, 17(2):e70026, 2026.

Natural Language Processing Psychometrics Cognitive networks for knowledge modeling: A gentle introduction for data-and cognitive scientists.Wiley Interdisciplinary Reviews: Cognitive Science, 17(2):e70026, 2026

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:40.737890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:40.737890Z digest=sha256:c911921957e8359953295f8af831323095c50f2f1d253ba3f54b238327d7ae25

Observation 2cf5ef69-a2a8-4090-87e4-44f5080a68b0 · outbound

This paper cites Cognitive network science: A review of research on cognition through the lens of network representations, processes, and dynamics.Complexity, 2019(1): 2108423, 2019.

Natural Language Processing Psychometrics Cognitive network science: A review of research on cognition through the lens of network representations, processes, and dynamics.Complexity, 2019(1): 2108423, 2019

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.389552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:40.796393Z digest=sha256:0a013370db66dccc6456e3bb2b364d7d7acb888dbc477c332ad90c287826ad30

Observation ad66a87e-3ba6-4476-af18-d14855be8861 · outbound

This paper cites spreadr: An r package to simulate spreading activation in a network.Behavior Research Methods, 51(2):910–929, 2019.

Natural Language Processing Psychometrics spreadr: An r package to simulate spreading activation in a network.Behavior Research Methods, 51(2):910–929, 2019

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:40.924130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:40.924130Z digest=sha256:74ba245bc7fd3892fd28a4e79f5352a9f94d859ae41b296435f6ef932e130530

Observation cc4f886b-3102-401d-b6be-d27832c9d47a · outbound

This paper cites Using network science in the language sciences and clinic.International journal of speech-language pathology, 17(1):13–25, 2015.

Natural Language Processing Psychometrics Using network science in the language sciences and clinic.International journal of speech-language pathology, 17(1):13–25, 2015

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.371992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:40.988974Z digest=sha256:16a26ccdc2c769d3587f992eb0a9431c6411cacd6af0cab95ce2dadaae892d39

Observation 91a1eb29-f1f2-4758-b868-8b698a89a4dc · outbound

This paper cites Crowdsourcing a word–emotion association lexicon.Computational intelligence, 29(3):436–465, 2013.

Natural Language Processing Psychometrics Crowdsourcing a word–emotion association lexicon.Computational intelligence, 29(3):436–465, 2013

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.088323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.088323Z digest=sha256:15531bb3cbff8cb0cb3fba7c5e7b90c58a67605fc47c83840fafc314114e5656

Observation c3ca5b3c-1cab-4783-9fc3-621670bcd5d6 · outbound

This paper cites Affective biases in english are bi-dimensional.Cognition and Emotion, 29(7):1147–1167, 2015.

Natural Language Processing Psychometrics Affective biases in english are bi-dimensional.Cognition and Emotion, 29(7):1147–1167, 2015

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.354641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.093035Z digest=sha256:ff1d0ee94c94891893b397731d4942d75d2147d4d970963f79c1a89c3da77927

Observation 251bc3cc-f736-410d-a216-a7bbd23c4477 · outbound

This paper cites A perspective on explainable artificial intelligence methods: Shap and lime.Advanced Intelligent Systems, 7(1):2400304, 2025.

Natural Language Processing Psychometrics A perspective on explainable artificial intelligence methods: Shap and lime.Advanced Intelligent Systems, 7(1):2400304, 2025

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.342393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.096792Z digest=sha256:5e318b0653bd523197eb7a92d3cd7a198f484dd30d81daeb286a756e590ec2ef

Observation 85be87a0-6229-45d6-8f0e-431e1d57c138 · outbound

This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Nature machine intelligence, 1(5):206–215, 2019.

Natural Language Processing Psychometrics Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Nature machine intelligence, 1(5):206–215, 2019

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.100002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.100002Z digest=sha256:ce3a8321de7328704fbe0bef55b6d57c280184a191bd8ed773250bc3b0d1fe01

Observation 8f0a3023-d158-46bb-9b37-b2af2e28e8e9 · outbound

This paper cites Personality traits in large language models.Prepritnt, 2023.

Natural Language Processing Psychometrics Personality traits in large language models.Prepritnt, 2023

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.325525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.104154Z digest=sha256:4a8884d15dc4b124f0895e2d0f0df0b74cc92ba55e6cfa363807d384bf039fe5

Observation 1ea48700-1aa7-4c0b-baf1-80d0c63f041f · outbound

This paper cites The satisfaction with life scale.Journal of personality assessment, 49(1):71–75, 1985.

Natural Language Processing Psychometrics The satisfaction with life scale.Journal of personality assessment, 49(1):71–75, 1985

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.314584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.108383Z digest=sha256:c790f8019984cd2abe33795dcecdd2a44b8df39f51495eaa9632b1b3bd95d502

Observation 2988692f-c7c7-4cce-b445-8366366199a9 · outbound

This paper cites Screening for depressive disorders in patients with skin diseases: a comparison of three screeners.Acta dermato-venereologica, 85(5):414–419, 2005.

Natural Language Processing Psychometrics Screening for depressive disorders in patients with skin diseases: a comparison of three screeners.Acta dermato-venereologica, 85(5):414–419, 2005

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.303080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.111998Z digest=sha256:54a2e449800a8913d740564dc881c3a317f12dc342e4b9bb5463a0710ba0b4b2

Observation 5a4e414b-f635-4e02-ad16-ca90fa87eca4 · outbound

This paper cites Advanced natural-based interaction for the italian language: Llamantino-3-anita, 2024.

Natural Language Processing Psychometrics Advanced natural-based interaction for the italian language: Llamantino-3-anita, 2024

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.290561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.115162Z digest=sha256:24c5decf4f5da6a8b2e2a29481efba60b44046154c056a0a70603c99e574caaa

Observation d365e7c6-ff3a-4791-ae00-f13eeb2bbd2a · outbound

This paper cites Qwen3 Technical Report.

Natural Language Processing Psychometrics Qwen3 Technical Report

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.119152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.119152Z digest=sha256:7fc65e1a8550deedc25e7ae8fdaa2dcb1f948ea6d69c1ea50c266a5f061b400a

Observation 87e3f56a-c0a5-4971-9ed0-2da3ed65b15c · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

Natural Language Processing Psychometrics gpt-oss-120b & gpt-oss-20b Model Card

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.123359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.123359Z digest=sha256:ea8bbf856ee6ae381a0b975c087300ba43d85a9e47e53cf7c0e7f7ee98e9470e

Observation 4ee601a7-7b0e-4051-b375-bac761ac13a8 · outbound

This paper cites Olmo 3.

Natural Language Processing Psychometrics Olmo 3

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.127297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.127297Z digest=sha256:bdb1abce96aa0a9cf6543a21682254cdf65f1e05d6d493d3fd1986d71aad0eb0

Observation 1f65dbe9-8136-454b-9a87-ac1a57dd728b · outbound

This paper cites Nemotron 3 nano: Open, efficient mixture-of-experts hybrid mamba-transformer model for agentic reasoning.arXiv preprint arXiv:2512.20848, 2025.

Natural Language Processing Psychometrics Nemotron 3 nano: Open, efficient mixture-of-experts hybrid mamba-transformer model for agentic reasoning.arXiv preprint arXiv:2512.20848, 2025

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.131797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.131797Z digest=sha256:fb843dde01e5eb771c806a46aff4366e8a81066c476eacf469c5c941cceef0bd

Observation 772ce7ed-0677-4896-8dbb-8c28eb1a78ea · outbound

This paper cites Testing theory of mind in large language models and humans.Nature Human Behaviour, 8(7):1285–1295, 2024.

Natural Language Processing Psychometrics Testing theory of mind in large language models and humans.Nature Human Behaviour, 8(7):1285–1295, 2024

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.135387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.135387Z digest=sha256:5efa203e30dceaeef8f0876fe390c95eceb6df62db59f45df7b76d822ff2c14a

Observation 2891d5a2-9566-40e1-baa6-920498691732 · outbound

This paper cites Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children’s understanding of deception.Cognition, 13(1):103–128, 1983.

Natural Language Processing Psychometrics Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children’s understanding of deception.Cognition, 13(1):103–128, 1983

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.139114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.139114Z digest=sha256:a2e7262d81567843b8d4d8482d2d5d7dfdbed404aa931c92371a250a505d276a

Observation 286ce5b3-ab85-48c7-be3f-2b2e6436d7ee · outbound

This paper cites Comparative performance of large language models in emotional safety classification across sizes and tasks.Frontiers in Artificial Intelligence, 8:1706090, 2025.

Natural Language Processing Psychometrics Comparative performance of large language models in emotional safety classification across sizes and tasks.Frontiers in Artificial Intelligence, 8:1706090, 2025

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.266097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.143105Z digest=sha256:59a6bcef5ad7819090e961cc91dfbfccafb6ea55982ff5c4c38b766b11b6eeb9

Observation 5e571775-b1df-4571-8df4-7ea977499722 · outbound

This paper cites The cost of thinking is similar between large reasoning models and humans.Proceedings of the National Academy of Sciences, 122(47):e2520077122, 2025.

Natural Language Processing Psychometrics The cost of thinking is similar between large reasoning models and humans.Proceedings of the National Academy of Sciences, 122(47):e2520077122, 2025

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.254452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.146839Z digest=sha256:6fc8bafcec7bdc405dc8d7882231d710a5d13b20293cda50c4ac6d0339b0fa09

Observation 7ba107b5-a3a3-4f2c-b27e-20a9e659d7a5 · outbound

This paper cites Language models don’t always say what they think: Unfaithful explanations in chain-of-thought prompting.Advances in Neural Information Processing Systems, 36:74952–74965, 2023.

Natural Language Processing Psychometrics Language models don’t always say what they think: Unfaithful explanations in chain-of-thought prompting.Advances in Neural Information Processing Systems, 36:74952–74965, 2023

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.150974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.150974Z digest=sha256:8ac443e6abdfc252beff216814c9354141e08f162f630fbe79fda8c65e26bf12

Observation 0f831512-5a67-44a4-8b76-a2d167a564b3 · outbound

This paper cites Leveraging llm respondents for item evaluation: A psychometric analysis.British Journal of Educational Technology, 56(3):1028–1052, 2025.

Natural Language Processing Psychometrics Leveraging llm respondents for item evaluation: A psychometric analysis.British Journal of Educational Technology, 56(3):1028–1052, 2025

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:43.048716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.154805Z digest=sha256:9fe488ab0378068d14a1c63c885e2d45e84330b2325f1d2a29b89fb5e301d65e

Observation da468584-2257-417e-8976-1dbdbef141d2 · outbound

This paper cites Covid-19 pandemic and lockdown measures impact on mental health among the general population in italy.Frontiers in psychiatry, 11:550552, 2020.

Natural Language Processing Psychometrics Covid-19 pandemic and lockdown measures impact on mental health among the general population in italy.Frontiers in psychiatry, 11:550552, 2020

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.930363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.158862Z digest=sha256:997a36b0774c7eb0d3386e9c21659098e9a8f8580da7765e6ee33c2d8c217724

Observation a89d959a-ddba-4516-8636-78e6f11820b1 · outbound

This paper cites Psychological distress among italians during the 2019 coronavirus disease (covid-19) quarantine.

Natural Language Processing Psychometrics Psychological distress among italians during the 2019 coronavirus disease (covid-19) quarantine

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.918955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.162730Z digest=sha256:555e95fd588f17c96daa39b8f706964d58cc36835c3034625a1f8cba27dd3f4b

Observation 86122838-c440-46d0-b908-c99a2f9782a7 · outbound

This paper cites Text-mining forma mentis networks reconstruct public perception of the stem gender gap in social media.PeerJ Computer Science, 6:e295, 2020.

Natural Language Processing Psychometrics Text-mining forma mentis networks reconstruct public perception of the stem gender gap in social media.PeerJ Computer Science, 6:e295, 2020

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.907785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.167595Z digest=sha256:dba3f3fb7f78ff9bc1386fcc725f3038ac88e11c1eba732c06b6559d5fa1f109

Observation 1f3fcafb-e9b8-4715-87ed-25e69985d074 · outbound

This paper cites Textual forma mentis networks bridge language structure, emotional content and psychopathology levels in adolescents.

Natural Language Processing Psychometrics Textual forma mentis networks bridge language structure, emotional content and psychopathology levels in adolescents

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.171706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.171706Z digest=sha256:6b31031d78d0722dbb607ed4afa4d2b163e7e0ddb89b9f2deeeb926a82ffefd0

Observation 3ee080ee-67d9-4ec1-8b8a-829736ccda8a · outbound

This paper cites Cognitive networks for knowledge modelling: A gentle tutorial for data-and cognitive scientists.PsyArXiv Preprints, 2023.

Natural Language Processing Psychometrics Cognitive networks for knowledge modelling: A gentle tutorial for data-and cognitive scientists.PsyArXiv Preprints, 2023

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.215131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.215131Z digest=sha256:56df967e2a44b9a74d2cdd9af0a62837d8169bc742980d6980132bad22095e40

Observation 8e281c28-ed1d-4326-9750-9fe37a49411e · outbound

This paper cites Estimating the number of communities in a network.Physical review letters, 117(7):078301, 2016.

Natural Language Processing Psychometrics Estimating the number of communities in a network.Physical review letters, 117(7):078301, 2016

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.889918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.245231Z digest=sha256:5502e40be4b49eb5c858f70a349e5001fd6cb173ea6c481890e5cc4ee7ee1674

Observation 578bd05d-672c-4cbf-a7a8-6125bcb0147d · outbound

This paper cites Ysocial: An artificial intelligence powered social media virtual twin.

Natural Language Processing Psychometrics Ysocial: An artificial intelligence powered social media virtual twin

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.878424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.283877Z digest=sha256:0c98ac784c7cd133d72e5bd443952c262ef74a11fa1a547a341f5ee1577b73c8

Observation fe62c558-100a-4e5f-beb5-ac322a7d5d49 · outbound

This paper cites Forma mentis networks quantify crucial differences in stem perception between students and experts.PloS one, 14(10):e0222870, 2019.

Natural Language Processing Psychometrics Forma mentis networks quantify crucial differences in stem perception between students and experts.PloS one, 14(10):e0222870, 2019

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.867283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.338208Z digest=sha256:25885b43e7de39e6a73d3ec6147d50d3f98829b6663e3c02e140ed5412876617

Observation 40693c3f-35c8-4506-a55a-ee462a0e5c70 · outbound

This paper cites A general psychoevolutionary theory of emotion.

Natural Language Processing Psychometrics A general psychoevolutionary theory of emotion

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.854579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.448700Z digest=sha256:d7951b0a6cd9685db21fee84933d2d2d299cc7c421053de770f014db7f5be6b5

Observation 49ad7173-b992-4d7b-ae56-9b56fc8760f5 · outbound

This paper cites Random forests.Machine learning, 45(1):5–32, 2001.

Natural Language Processing Psychometrics Random forests.Machine learning, 45(1):5–32, 2001

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.536895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.536895Z digest=sha256:379194ca2b42e878440f4d3f7bf52cce0ea32504dcbf4f18c35da1999983b6b2

Observation 2b9d3fbc-ce7f-4038-96ca-12c050600a63 · outbound

This paper cites Pedregosa, G.

Natural Language Processing Psychometrics Pedregosa, G

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.541057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.541057Z digest=sha256:4b938e8448128fe5fa95e7323bea1d050dbb1646bba2cc1e9105db81e09b589d

Observation 5a613955-6238-4864-8e0e-a9441b5e3d53 · outbound

This paper cites A unified approach to interpreting model predictions.Advances in neural information processing systems, 30, 2017.

Natural Language Processing Psychometrics A unified approach to interpreting model predictions.Advances in neural information processing systems, 30, 2017

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.544131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.544131Z digest=sha256:d37d920283a3e16f56c4e1d917d16b77faf9dcdf5e1ffa5b895fce5d6517c407

Observation ae93cdf0-160b-4d3a-bc17-2b7237749f2c · outbound

This paper cites From local explanations to global understanding with explainable ai for trees.Nature machine intelligence, 2(1):56–67, 2020.

Natural Language Processing Psychometrics From local explanations to global understanding with explainable ai for trees.Nature machine intelligence, 2(1):56–67, 2020

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.547989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.547989Z digest=sha256:0f91af1e88745802e62220460f1361e8741c964cf7a36434b47387d400a82542

Observation e387df7d-06e3-4374-bf37-cc2f1f828ef7 · outbound

This paper cites Do models of mental health based on social media data generalize? InFindings of the association for computational linguistics: EMNLP 2020, pages 3774–3788, 2020.

Natural Language Processing Psychometrics Do models of mental health based on social media data generalize? InFindings of the association for computational linguistics: EMNLP 2020, pages 3774–3788, 2020

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.816900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.551717Z digest=sha256:4ce5ec50071a5613a66f81a283d1f31f5a83ca15f7f0b9c5aa091e101b6db2d9

Observation 85d22da5-4315-441d-94e3-96ab2079a945 · outbound

This paper cites The androids corpus: A new publicly available benchmark for speech based depression detection.Depression, 47:11–9, 2023.

Natural Language Processing Psychometrics The androids corpus: A new publicly available benchmark for speech based depression detection.Depression, 47:11–9, 2023

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.804327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.555012Z digest=sha256:97cc8e09c8979fd8b51cdfa2bc224bf32933597b5c870c9815d718e0c0c686da

Observation b01bf2db-b2e6-4285-83e9-ce6baa6d25d0 · outbound

This paper cites Robust speech recognition via large-scale weak supervision.

Natural Language Processing Psychometrics Robust speech recognition via large-scale weak supervision

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-10T10:28:41.558761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.558761Z digest=sha256:93cee0b2a401d796e64f1e74206a8b8b9f6277a87aa3904bdb6d3ffa1392091d

Observation 55cb1972-f9c1-434a-8f86-8355c5cdfa3c · outbound

This paper cites Modeling depressive patterns in italian discourse: Insights from natural language processing, 2025.

Natural Language Processing Psychometrics Modeling depressive patterns in italian discourse: Insights from natural language processing, 2025

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.649849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.562681Z digest=sha256:b15bcfb077656be98054ee6a42ee8d50cfebab86e442a5d8870dc28477782306

Observation e83b2c94-7e43-4d47-bedd-932cf4f233f9 · outbound

This paper cites Will money increase subjective well-being?Social indicators research, 57 (2):119–169, 2002.

Natural Language Processing Psychometrics Will money increase subjective well-being?Social indicators research, 57 (2):119–169, 2002

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.413329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.566447Z digest=sha256:f2a569e4bcb6326c5e90cc7569fb68dcc55e7a2bc07fd2eb07a28effa8a6cbd7

Observation aa28470c-b91c-457d-94ed-c45994a9156f · outbound

This paper cites High income improves evaluation of life but not emotional well-being.

Natural Language Processing Psychometrics High income improves evaluation of life but not emotional well-being

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.309060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.570564Z digest=sha256:13b0d5ec1b3ee301e4348a95263368d62877b5a82bfa7ec2d3f01ae5e4d63d8e

Observation cbd0be37-7256-4b46-9fc1-800b333ddbc6 · outbound

This paper cites Happiness, income satiation and turning points around the world.Nature Human Behaviour, 2(1):33–38, 2018.

Natural Language Processing Psychometrics Happiness, income satiation and turning points around the world.Nature Human Behaviour, 2(1):33–38, 2018

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.279502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.574477Z digest=sha256:998c3caf67aa8ca5b46bbd3a1baaeb16b60082bf5240f66acc4e67dc8377f073

Observation c603d5c2-ce5a-440f-a8c9-2d327a4fb5e7 · outbound

This paper cites Sadness as an integral part of depression.Dialogues in clinical neuroscience, 10(3):321–327, 2008.

Natural Language Processing Psychometrics Sadness as an integral part of depression.Dialogues in clinical neuroscience, 10(3):321–327, 2008

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.268906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.578159Z digest=sha256:c11d43e049aee7a472d51a902027491553d3ba50ae560be830bec61fcdf7c3dc

Observation 5355d85a-64a1-4a37-890c-d2d288cc45b9 · outbound

This paper cites American psychiatric association Washington, DC, 2013.

Natural Language Processing Psychometrics American psychiatric association Washington, DC, 2013

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.258188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.581791Z digest=sha256:9a2b7834c64f296c15bba1d953365540708052e12fb47cf1584745ceaa4daf5e

Observation fc151111-4acd-4b00-aff0-7b2cad490c66 · outbound

This paper cites Language use of depressed and depression-vulnerable college students.Cognition & Emotion, 18(8):1121–1133, 2004.

Natural Language Processing Psychometrics Language use of depressed and depression-vulnerable college students.Cognition & Emotion, 18(8):1121–1133, 2004

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.247800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.585998Z digest=sha256:f438eeb7800bd10e0699322713d2ea48f269a259d09d2757ce946b90aab3d381

Observation fcbf0943-85c3-427e-b31c-4aebc65f7b51 · outbound

This paper cites Facebook language predicts depression in medical records.

Natural Language Processing Psychometrics Facebook language predicts depression in medical records

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.236207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.589813Z digest=sha256:364b4db2ab250953414e2dc83871ad558f6b826900db67360f1b3c0bab147e16

Observation 8353271d-f910-4e82-9824-080189c87371 · outbound

This paper cites Constructive and unconstructive repetitive thought.Psychological bulletin, 134(2):163, 2008.

Natural Language Processing Psychometrics Constructive and unconstructive repetitive thought.Psychological bulletin, 134(2):163, 2008

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.224957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.593220Z digest=sha256:2c85102c33c1907e85482cb934f94682b8848ffe0582961280f60cd27c0e66f7

Observation a99c1966-41bf-4c41-80f7-a14cab9c2a19 · outbound

This paper cites Language-based personality: A new approach to personality in a digital world.Current opinion in behavioral sciences, 18:63–68, 2017.

Natural Language Processing Psychometrics Language-based personality: A new approach to personality in a digital world.Current opinion in behavioral sciences, 18:63–68, 2017

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.212581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.597120Z digest=sha256:7efc28a8e494745d71330d5ead0eba0962f4e84aa074a08a23ea0c5c7ac2fd0f

Observation bafbda36-e1d9-48c2-ae72-3b75ba42e21e · outbound

This paper cites Forma mentis networks map how nursing and engineering students enhance their mindsets about innovation and health during professional growth.PeerJ Computer Science, 6:e255, 2020.

Natural Language Processing Psychometrics Forma mentis networks map how nursing and engineering students enhance their mindsets about innovation and health during professional growth.PeerJ Computer Science, 6:e255, 2020

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.200465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.600371Z digest=sha256:00e532b04a486ffa8f37c068e3f9a9caf5072415fc8de875c1df26cb59996441

Observation 17c17327-466d-4a05-aa4a-0f748cc4c8cc · outbound

This paper cites Rethinking rumination.Perspectives on psychological science, 3(5):400–424, 2008.

Natural Language Processing Psychometrics Rethinking rumination.Perspectives on psychological science, 3(5):400–424, 2008

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.187572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.603589Z digest=sha256:2ca551f5be2f6a97340712a058be54737398d164b7736fe33c03a4192806df9c

Observation 688efb6d-b949-4444-bb31-5f321cf2c2c4 · outbound

This paper cites Linking “big” personality traits to anxiety, depressive, and substance use disorders: a meta-analysis.Psychological bulletin, 136(5):768, 2010.

Natural Language Processing Psychometrics Linking “big” personality traits to anxiety, depressive, and substance use disorders: a meta-analysis.Psychological bulletin, 136(5):768, 2010

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.174390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.607092Z digest=sha256:d2e8c0fb2a777df81cb380c1625be52c75b39c0d9c33b9b20f5e34c16ef0ed25

Observation f8b9f734-9610-4284-9b6a-87ffaa85ba0f · outbound

This paper cites Worry: A cognitive phenomenon intimately linked to affective, physiological, and interpersonal behavioral processes.Cognitive therapy and research, 22(6):561–576, 1998.

Natural Language Processing Psychometrics Worry: A cognitive phenomenon intimately linked to affective, physiological, and interpersonal behavioral processes.Cognitive therapy and research, 22(6):561–576, 1998

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T10:28:42.160120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:41.610102Z digest=sha256:43bfcb7c03df0bc0e240eb6e93e25cd3959e6aacae48a3db406be0ac70fad987

Observation 6664000f-0e31-445a-8cfb-36887ef7c485 · outbound

This paper cites Machine Psychology.

Natural Language Processing Psychometrics Machine Psychology

Reference 91

Resolution
malformed identifier
no resolver link, observed 2026-08-10T10:28:41.613505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:28:41.613505Z digest=sha256:0a4969d365184e012c4c0291e50acff7c5ac451accb8c2a778ec8b2db46f11f3

Observation 69507402-af41-4018-8d58-e13d7fc6044c · outbound

This paper cites an unresolved cited work.

Natural Language Processing Psychometrics Unresolved cited work

Reference 2026

Resolution
verified exact
doi, observed 2026-08-10T10:28:41.648987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T10:28:40.654635Z digest=sha256:7e836935fc2f862323e750a0c48eb28c97177434f45b3508f98b0a9d41f70fe2

Pith citing papers

No inbound Pith citation observations are available.