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  1. 441
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    Discrepancy Between Fingertip Glucose Levels and HbA1c in an Adolescent with Diabetes: A Fake Logbook or Pseudohypoglycemia?
  2. 442
    por Orhan, Ali
    Publicado 2023
    “…Sosu Critical Thinking Dispositions Scale, New Media Literacy Scale, and fake news detection task were employed to gather the data. …”
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    Fake news detection on social media: the predictive role of university students’ critical thinking dispositions and new media literacy
  3. 443
    “…RESULTS: CoronaAI was widely accessed by users in search of valuable and updated information on COVID-19, including checking the veracity of possible fake news about the spread of cases, deaths, symptoms, tests and protocols, among others. …”
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    How people interact with a chatbot against disinformation and fake news in COVID-19 in Brazil: The CoronaAI case
  4. 444
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    Use of Grading of Recommendations, Assessment, Development, and Evaluation to Combat Fake News: A Case Study of Influenza Vaccination in Pregnancy
  5. 445
    por King, Anthony
    Publicado 2020
    “…The downside is the risk of spreading false information or fake news though.[Image: see text]…”
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    Fast news or fake news?: The advantages and the pitfalls of rapid publication through pre‐print servers during a pandemic
  6. 446
    por Neuwirth, Rostam J.
    Publicado 2021
    “…Based on the qualification of “fake news” as an oxymoron, this article critically examines the deficiencies in a dichotomous distinction between fact and fiction exemplified by information about the pandemic of coronavirus disease 2019 (Covid-19) in an attempt to clarify the principal issues for a global regulatory debate regarding “fake news”.…”
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    The Global Regulation of “Fake News” in the Time of Oxymora: Facts and Fictions about the Covid-19 Pandemic as Coincidences or Predictive Programming?
  7. 447
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    Mitigating infodemics: The relationship between news exposure and trust and belief in COVID-19 fake news and social media spreading
  8. 448
    por Ren, Zhong, Liu, Tao, Liu, Guodong
    Publicado 2021
    “…In this work, photoacoustic spectroscopy was employed to distinguish real blood from fake blood rapidly, accurately, and recoverably. …”
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    Classification and discrimination of real and fake blood based on photoacoustic spectroscopy combined with particle swarm optimized wavelet neural networks
  9. 449
    “…Studies that addressed the impact of fake news on patients and healthcare professionals around the world were included. …”
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    The impact of fake news on social media and its influence on health during the COVID-19 pandemic: a systematic review
  10. 450
    “…First, we verified that SVM algorithms are incapable of identifying hacking by simulating a set of cyberattacks using fake P300 signals and noise-based attacks. This was achieved by comparing the performance of several models when validated using real and hacked P300 datasets. …”
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    A Cybersecure P300-Based Brain-to-Computer Interface against Noise-Based and Fake P300 Cyberattacks
  11. 451
    “…RESULTS: Morality (R2 = 0.08, p < 0.001), social cognition (R2 = 0.05, p < 0.05), and political and religious orientation (R2 = 0.1, p < 0.000001) predicted belief in COVID-19 fake news. On the other hand, no variables were found to predict belief in fake news unrelated to the pandemic. …”
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    Fake News and social Cognition During The SARS-COV-2 Pandemic: Initial Approach Towards understanding Belief In Misinformation
  12. 452
    “…As the COVID-19 pandemic sweeps across the world, it has been accompanied by a tsunami of fake news and misinformation on social media. At the time when reliable information is vital for public health and safety, COVID-19 related fake news has been spreading even faster than the facts. …”
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    Cross-SEAN: A cross-stitch semi-supervised neural attention model for COVID-19 fake news detection
  13. 453
    “…Fake news often carries negative sentiments, and the public’s response to it carries the emotions of surprise, fear, and disgust. …”
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    Fake News Detection Model on Social Media by Leveraging Sentiment Analysis of News Content and Emotion Analysis of Users’ Comments
  14. 454
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    Editorial: The psychology of fake news on social media, who falls for it, who shares it, why, and can we help users detect it?
  15. 455
    “…OBJECTIVE: The present study tested the combination of an established and a validated food-choice research method (the ‘fake food buffet’) with a new food-matching technology to automate the data collection and analysis. …”
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    Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment
  16. 456
    “…CONCLUSIONS: These findings are especially relevant to health care organizations seeking to combat a recent rise in fake patient reviews. Providing patients with realistic expectations of the care that clinicians can offer via their own online biographical videos can help counteract negative patient comments online.…”
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    The Buffering Effect of Health Care Provider Video Biographies When Viewed in Combination With Negative Reviews: “You Can’t Fake Nice”
  17. 457
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    Fake gunshot wounds in the skull—post-mortem artifact caused by steel probe during police search for a missing body
  18. 458
    “…BACKGROUND: Although fake news creation and consumption are mutually related and can be changed to one another, our review indicates that a significant amount of research has primarily focused on news creation. …”
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    A systematic review on fake news research through the lens of news creation and consumption: Research efforts, challenges, and future directions
  19. 459
    por Zhang, Chong, Cao, Tong, Ali, Asad
    Publicado 2022
    “…Perceived COVID-19 information overload has a positive impact on COVID-19 fear. In addition, fake news related to COVID-19 strengthens the relationship between perceived COVID-19 information overload and COVID-19 fear. …”
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    Investigating the Role of Perceived Information Overload on COVID-19 Fear: A Moderation Role of Fake News Related to COVID-19
  20. 460
    “…Herein we describe a combo of two novel methods to distinguish genuine saffron from fake in a user-friendly manner and without sophisticated instruments. …”
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    The menace of saffron adulteration: Low-cost rapid identification of fake look-alike saffron using Foldscope and machine learning technology
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