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相关概念视频

The Scientific Method01:32

The Scientific Method

227.4K
The scientific method is a detailed, empirical problem-solving process used by biologists and other scientists. This iterative approach involves formulating a question based on observation, developing a testable potential explanation for the observation (called a hypothesis), making and testing predictions based on the hypothesis, and using the findings to create new hypotheses and predictions.
Generally, predictions are tested using carefully-designed experiments. Based on the outcome of these...
227.4K
Accuracy and Precision01:52

Accuracy and Precision

8.9K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.  Highly accurate...
8.9K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

349
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
349
Improving Translational Accuracy02:07

Improving Translational Accuracy

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2.6K
Causality in Epidemiology01:21

Causality in Epidemiology

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Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
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相关实验视频

Updated: Jul 17, 2025

An Open Source Technology Platform to Manufacture Hydrogel-Based 3D Culture Models in an Automated and Standardized Fashion
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An Open Source Technology Platform to Manufacture Hydrogel-Based 3D Culture Models in an Automated and Standardized Fashion

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推准确的科学沟通.

Aurélien Allard1, Christine Clavien1

  • 1iEH2-Institute for Ethics History Humanities, University of Geneva, Geneva, Switzerland.

PloS one
|August 31, 2023
PubMed
概括
此摘要是机器生成的。

推动和社会激励措施未能改善诚实的科学新闻传播. 参与者表现出对积极结果的偏见和确认偏见,激励措施加剧了这些趋势.

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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Author Spotlight: Biological Standardization to Ensure Reproducibility and Harmonization in Research
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Author Spotlight: Biological Standardization to Ensure Reproducibility and Harmonization in Research

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相关实验视频

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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Author Spotlight: Biological Standardization to Ensure Reproducibility and Harmonization in Research
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科学领域:

  • 社会科学 社会科学 社会科学
  • 生物医学科学 生物医学科学
  • 科学沟通科学沟通

背景情况:

  • 科学界面临着可复制性危机,需要改善研究成果的诚实传输.
  • 确保科学新闻的准确报道对于公众对科学的理解和信任至关重要.

研究的目的:

  • 调查推动和软社会激励是否可以增强选择高质量的科学新闻进行报道.
  • 评估这些干预措施对减轻科学新闻中的偏见的影响.

主要方法:

  • 两个在线随机实验,有2425名参与者担任科学记者.
  • 参与者在结果相反的研究和不同可信度标志物 (样本大小,设计) 之间进行选择.
  • 软框架推动和社会激励被用来影响对或反对可信的科学传播的选择.

主要成果:

  • 参与者更喜欢采用大样本和随机设计的研究.
  • 观察到对积极结果和确认偏差 (偏好与先前信念一致的结果) 的显著偏差.
  • 推动和社会激励都没有有效地抵消这些偏见;反对诚实传播的社会激励加剧了这些偏见.

结论:

  • 标准的可信度标记不足以防止科学研究被偏地选择作为报告.
  • 软框架的推动和社会激励在促进科学新闻的诚实传播方面是无效的.
  • 旨在改善科学传播的干预措施必须更直接地解决潜在的认知偏见.