Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T04:25:23.678175Z
Paper Citation Record · LEDGER
As of 19 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2507.08002.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T04:25:23.678175Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
44 of 44 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation bf300844-a319-49a1-9696-fa99a11e5836 · outbound
Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study (2025) Karisa Parkington*, Bazen G
Reference 1
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Reference 2
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Panel A: Frequency comparison of codes and themes
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Using thematic analysis in psychology,
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Pragmatic measures: what they are and why we need them,
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Studying complexity in health services research: desperately seeking an overdue paradigm shift,
Reference 9
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Qualitative methods in implementation research: An introduction,
Reference 10
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study What Is Qualitative Research? An Overview and Guidelines,
Reference 12
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study,
Reference 14
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Best practices for implementing ChatGPT, large language models, and artificial intelligence in qualitative and survey-based research,
Reference 15
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Observation 6b0531d7-a518-464c-8590-f25752ad1419 · outbound
Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Exploring the Use of AI in Qualitative Analysis: A Comparative Study of Guaranteed Income Data,
Reference 16
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Qualitative and mixed methods in mental health services and implementation research,
Reference 17
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis
Reference 18
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Comparing GPT-4 and Human Researchers in Health Care Data Analysis: Qualitative Description Study,
Reference 19
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study A Review on Large Language Models: Architectures, Applications, Taxonomies, Open Issues and Challenges,
Reference 20
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Job-Related Problems Prior to Nurse Suicide, 2003-2017: A Mixed Methods Analysis Using Natural Language Processing and Thematic Analysis,
Reference 21
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Thematic analysis and natural language processing of job-related problems prior to physician suicide in 2003-2018,
Reference 22
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Inductive thematic analysis of healthcare qualitative interviews using open-source large language models: How does it compare to traditional methods?,
Reference 23
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Performing an Inductive Thematic Analysis of Semi-Structured Interviews With a Large Language Model: An Exploration and Provocation on the Limits of the Approach,
Reference 24
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Can Large Language Models Understand Context?
Reference 26
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Long short-term memory,
Reference 27
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Observation 53e85435-01e5-41ec-bad4-cb7e93e11959 · outbound
Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Current applications and challenges in large language models for patient care: A systematic review,
Reference 29
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Observation 024927c1-0d65-4f1a-b7ff-83e37f61c267 · outbound
Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Qualitative data analysis in the age of artificial general intelligence,
Reference 30
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Clinician voices on ethics of LLM integration in healthcare: a 10 thematic analysis of ethical concerns and implications,
Reference 31
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Observation 33f3d04e-521b-43bb-af1a-10f0d8c4fd11 · outbound
Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Benefits and Harms of Large Language Models in Digital Mental Health
Reference 33
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study AI–Human Hybrids for Marketing Research: Leveraging Large Language Models (LLMs) as Collaborators,
Reference 34
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Applications of large language models in psychiatry: A systematic review,
Reference 35
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Analyzing patient perspectives with large language models: a cross-sectional study of sentiment and thematic classification on exception from informed consent,
Reference 36
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Digital Interventions to Understand and Mitigate Stress Response: Protocol for Process and Content Evaluation of a Cohort Study,
Reference 37
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Observation 2b31f86a-9d43-4472-84e5-6ad955cc4fb0 · outbound
Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study From bard to Gemini: An investigative exploration journey through Google’s evolution in conversational AI and generative AI,
Reference 38
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Created in BioRender
Reference 39
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Prompts, Pearls, Imperfections: Comparing ChatGPT and a Human Researcher in Qualitative Data Analysis,
Reference 40
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study The art of prompting: Unleashing the power of large language models,
Reference 41
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Unresolved cited work
Reference 42
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Reference 47
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Available: https://www.audiotranskription.de/wp-content/uploads/2020/11/manual-on-transcription.pdf
Reference 2015
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Attention Is All You Need
Reference 2017
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Language Models are Few-Shot Learners
Reference 2020
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Reference 2021
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies
Reference 2023
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Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Using ChatGPT for Thematic Analysis
Reference 2024
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No inbound Pith citation observations are available.