Survey Background and Objectives
• Scientific theories allow us to model the universe around us and provide a framework to understand nature. While the models we develop are only as accurate as their underlying assumptions, their real value lies in their capacity to provide a more useful understanding of nature. New models are rightly viewed with a degree of skepticism until they demonstrate the ability to accurately interpret existing data, resolve shortcomings in current models and successfully predict and interpret new data.
• The charge fiber model presented here is being developed outside the auspices of traditional university research programs and the most well known physics conferences and journal publications. As such, the majority of academics, researchers and scientists in the field have not likely heard of it. This approach, along with the model's extensive and sweeping claims, is reason enough for many to dismiss it as quackery and unscientific rambling. One has to ask: How is the charge fiber model different from other proposals found on the web that purport to have reinvented physics in some degree or other?
• Fortunately, some of the differences between an emerging scientific model that is sound and one that is mere hyperbole are not hard to identify: Is the model supported by conventional mathematics? Are detailed mathematical derivations available to be examined and checked? Does the model accurately interpret existing data? Does the model better resolve issues that current models struggle with? Are there experimental results that differentiate the new model from existing models? Can the experimental results be independently verified?
This survey project has four objectives:
1) Provide an overview of the charge fiber model for academics, researchers, scientists, and graduate students.
2) Contact people who are experts in the field and ask what they know about the model and their opinions of it.
3) Provide links to resources for further investigation of the model.
4) Solicit practical ideas for experiments to validate or invalidate the model.