Butterfly Effect; Genetics of Weight Loss; Artificial Intelligence in Medicine

A Linear System or Model is any physical system that can be described as acting in ways that only use straight lines. Mathematically, a linear system can be described by one or more formulas of the form y = mx + b.

A Non-Linear System or Model is any physical system that cannot be described as acting in ways that only use straight lines, but also requires curves. Mathematically a non-linear system requires more complex equations that are harder to work with.

Extrapolation is the process of using some known data (and a mathematical model) to project to a result far away from the available data. The farther the projection, the more error is introduced and the less reliable the result. Extrapolation in non-linear systems is especially difficult to do.

Interpolation is the process of using some known data (and a mathematical model) to project to a result intermediate between the known data. This is much more reliable that extrapolation.

An Ill-conditioned System is any physical system or model in which small changes in the input parameters causes large, seemingly random changes in observed results. Ill-conditioned systems are generally unpredictable; computer models based on ill-conditioned systems are generally of limited practical value.

Chaos Theory is the mathematical discipline dedicated to the study of ill-conditioned systems, including fractals and the butterfly effect.

The butterfly effect is a description of ill-conditioned climate and weather systems. The premise is that even so small of a change in the input parameters as a change in the way a butterfly flaps its wings in China can result in dramatic, unpredictable, changes in an ill-conditioned weather or climate model, such as causing a flood OR drought in Payson, AZ.

The butterfly effect was discussed in the movie Jurassic Park, which was written by Dr. Michael Crichton, a Harvard Medical School graduated turned author/director.

According to IBM, "Monte Carlo Simulation, also known as the Monte Carlo Method or a multiple probability simulation, is a mathematical technique, which is used to estimate the possible outcomes of an uncertain event. The Monte Carlo Method was invented by John von Neumann and Stanislaw Ulam during World War II to improve decision making under uncertain conditions."

This approach can be used to test the stability of the ill-conditioned climate models to small changes in experimental input data.

One major climate research facility, the "Climatic Research Unit" at University of East Anglia, UK refused to release the raw data and the algorithmic codes required by the scientific method for other scientists to independently verify the result.

This lack of transparency suggests a cover-up of "bad science," which is documented in the book "Climategate."

It is well known that alternating periods of global cooling and warming have been occurring for eons. Each cooling cycle is called an "ice age" which is inevitably separated from the next ice age by a period of "global warming."

These cycles have been repeating long before humanity invented the internal combustion engine.

Within the last 1,000 years we have had periods of warming and cooling, called the medieval warm period and the subsequent mini ice age.

An important factor in all climate models is the energy output from the sun, which is essential to the global warming process.

Unfortunately, the sun's output varies in an unpredictable way, so current climate models cannot account for the changes in energy output from the sun. This is documented in the book "Hot Talk, Cold Science"