AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns | Paper Citation Record

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This paper cites Writing Tools: Looking Back to Look Ahead.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Writing Tools: Looking Back to Look Ahead

Reference 1

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This paper cites Lin, ROUGE: A Package for Automatic Evaluation of Summaries, in Text Summarization Branches Out, pp.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Lin, ROUGE: A Package for Automatic Evaluation of Summaries, in Text Summarization Branches Out, pp

Reference 2

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This paper cites ROUGE 2.0: Updated and Improved Measures for Evaluation of Summarization Tasks.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns ROUGE 2.0: Updated and Improved Measures for Evaluation of Summarization Tasks

Reference 3

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This paper cites Towards AI-assisted Academic Writing.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Towards AI-assisted Academic Writing

Reference 4

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This paper cites Kavukcuoglu, Gemini 2.5: Our most intelligent AI model, Google.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Kavukcuoglu, Gemini 2.5: Our most intelligent AI model, Google

Reference 5

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Unresolved cited work

Reference 6

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This paper cites (May 22, 2025).

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (May 22, 2025)

Reference 7

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This paper cites AI-Driven Scholarly Peer Review via Persistent Workflow Prompting, Meta-Prompting, and Meta-Reasoning.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns AI-Driven Scholarly Peer Review via Persistent Workflow Prompting, Meta-Prompting, and Meta-Reasoning

Reference 8

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns LLM Context Conditioning and PWP Prompting for Multimodal Validation of Chemical Formulas

Reference 9

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This paper cites A Survey on In-context Learning.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns A Survey on In-context Learning

Reference 10

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This paper cites An Explanation of In-context Learning as Implicit Bayesian Inference.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns An Explanation of In-context Learning as Implicit Bayesian Inference

Reference 11

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Language Models are Few-Shot Learners

Reference 12

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Marvin, N

Reference 13

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Unleashing the potential of prompt engineering for large language models

Reference 14

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 15

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns The Prompt Report: A Systematic Survey of Prompt Engineering Techniques

Reference 16

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This paper cites Exploring Prompt Engineering: A Systematic Review with SWOT Analysis.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Exploring Prompt Engineering: A Systematic Review with SWOT Analysis

Reference 17

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This paper cites Autonomous Prompt Engineering in Large Language Models.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Autonomous Prompt Engineering in Large Language Models

Reference 18

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Large Language Models Are Human-Level Prompt Engineers

Reference 19

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This paper cites Self-Prompt Tuning: Enable Autonomous Role-Playing in LLMs.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Self-Prompt Tuning: Enable Autonomous Role-Playing in LLMs

Reference 20

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns The Unreasonable Effectiveness of Eccentric Automatic Prompts

Reference 21

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Swales, C.B

Reference 22

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This paper cites Borja, 11 steps to structuring a science paper editors will take seriously, Elsevier.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Borja, 11 steps to structuring a science paper editors will take seriously, Elsevier

Reference 23

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Unresolved cited work

Reference 24

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This paper cites https://apastyle.apa.org/products/publication-manual-7th-edition.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns https://apastyle.apa.org/products/publication-manual-7th-edition

Reference 25

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This paper cites O’Connor, F.P.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns O’Connor, F.P

Reference 26

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This paper cites Gastel, R.A.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Gastel, R.A

Reference 27

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns https://authorservices.taylorandfrancis.com/publishing-your-research/writing-your-paper/writing-a-journal- article/

Reference 28

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Alley, The Craft of Scientific Writing, 4th ed., Springer, New York, NY, 2018

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Ramadan, C

Reference 31

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Dedhe, H

Reference 32

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Unresolved cited work

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (In an Abstract, this often forms the opening statements; in Conclusions, it's typically a focused reminder of the core purpose or problem)

Reference 35

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (Essential for Abstracts; Conclusions would typically only mention methods if using Category 3)

Reference 36

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (More typical for Conclusions if a methodological point is a key takeaway)

Reference 37

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (Abstracts will present these very concisely)

Reference 38

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (Rare in Abstracts, more common in Conclusions if space and significance allow)

Reference 39

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (In an Abstract, interpretations are typically very concise and tied directly to key findings; Conclusions may offer slightly more elaborated summaries of interpretations)

Reference 40

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (In an Abstract, this is often a direct and concise statement)

Reference 41

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (Generally rare and very brief in Abstracts; more common in Conclusions as a summary of key comparisons from the Discussion)

Reference 42

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (A key component for both Abstracts and Conclusions)

Reference 43

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (May be very concise in Abstracts; more elaborated in Conclusions if based on Discussion)

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (Very rare in Abstracts; more common and important in Conclusions for balance)

Reference 45

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (May be very brief or absent in Abstracts; more common and detailed in Conclusions)

Reference 46

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Observation 80622443-45b8-473a-a94e-ac8e6f521ec5 · outbound

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns (This is the culminating statement for both Abstracts and Conclusions)

Reference 47

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AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Enrichment of H217O from Tap Water, Characterization of the Enriched Water, and Properties of Several 17O-Labeled Compounds

Reference 48

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This paper cites fair use.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns fair use

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Observation 90585872-5b73-41be-900c-f9ee9412ddf2 · outbound

This paper cites  Transformative Use: The work is not merely being reproduced; it is fundamentally repurposed as a research specimen for critical analysis.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns  Transformative Use: The work is not merely being reproduced; it is fundamentally repurposed as a research specimen for critical analysis

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:01.201747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e2fd38ac-fbc4-4035-9a68-76c8b379a9dc · outbound

This paper cites  However, the conducted analysis (central to this project) has revealed substantial flaws impacting the reliability and validity of the work's core research findings as presented.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns  However, the conducted analysis (central to this project) has revealed substantial flaws impacting the reliability and validity of the work's core research findings as presented

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:01.184416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 72b6b1ae-34a7-4c65-b688-189f52b4d85d · outbound

This paper cites Justification: This amount is essential and necessary for the stated purpose.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Justification: This amount is essential and necessary for the stated purpose

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:01.168346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9d977407-8efd-4204-81d5-e1a4e5de04d1 · outbound

This paper cites The publisher's market relies on the perceived value of the article as a source of valid scientific findings.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns The publisher's market relies on the perceived value of the article as a source of valid scientific findings

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:01.154069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7583a4f2-5029-4d2d-a1c4-35de464865bf · outbound

This paper cites This material is intended solely for the recipient(s) for purposes directly related to verifying, understanding, or building upon the presented critique and methodological research.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns This material is intended solely for the recipient(s) for purposes directly related to verifying, understanding, or building upon the presented critique and methodological research

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:01.139662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f338d78e-40e4-4a06-bf3c-dc89b108d6d2 · outbound

This paper cites Language Models are Few-Shot Learners.

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns Language Models are Few-Shot Learners

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T00:40:00.352969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers