Gab@StFerdinandIII - https://unstabbinated.substack.com/
Plenty of cults exist - every cult has its 'religious dogma', its idols, its 'prophets', its 'science', its 'proof' and its intolerant liturgy of demands. Cults everywhere: Corona, 'The Science' or Scientism, Islam, the State, the cult of Gender Fascism, Marxism, Darwin and Evolution, Globaloneywarming, Changing Climate, Abortion...
Tempus Fugit Memento Mori - Time Flies Remember Death
This is bad news for the cult of evolution. Flawed, if not criminally deficient models underpin the evolution cult and the cult of the climate and ‘warming’. There is no man-made climate crisis from the emissions of a trace chemical called plant food. There is also no evidence, observational, factual, laboratory or modelled, to support the religion of Darwin. One of the cult’s major platforms used in over 200.000 papers to support ‘evolutionary theory’, when actually investigated, is found fraudulent. This is no surprise. The cult of evolution has committed hundreds of criminal acts of deceit and mendacity. No surprise that their main ‘model’ is a scam.
Study reveals flaws in popular genetic method (Lund University, 30 Aug 2022).
Dr. Eran Elhaik, Associate Professor in molecular cell biology at Lund University, has analysed a model used in 60 years’ worth of genetic studies. The main method and logic within this model is called Principle Component Analysis (PCA), and it is a fraud.
The most common analytical method within population genetics is deeply flawed, according to a new study from Lund University in Sweden. This may have led to incorrect results and misconceptions about ethnicity and genetic relationships. The method has been used in hundreds of thousands of studies, affecting results within medical genetics and even commercial ancestry tests The study is published in Scientific Reports.
Between 32,000 and 216,000 scientific articles in genetics alone have employed PCA for exploring and visualizing similarities and differences between individuals and populations and based their conclusions on these results.
The source paper is open access for all to read and gasp at the implications. Elhaik, “Principal Component Analyses (PCA)-based findings in population genetic studies are highly biased and must be re-evaluated,”
Nature Scientific Reports volume 12, Article number: 14683 (2022). All the buzzwords used to support Darwin’s religion within 200.000 plus ‘studies’ are thereby fraudulent. They are premised on a purposefully built method to generate supporting evidence when none exist.
PCA’s widespread use could not have been achieved without several key traits that distinguish it from other tools—all tied to the replicability crisis. PCA can be applied to any numerical dataset, small or large, and it always yields results. It is parameter-free and nearly assumption-free. It does not involve measures of significance, effect size evaluations, or error estimates. It is, by large, a “black box” harbouring complex calculations that cannot be traced.
And
PCA serves as the primary tool to identify the origins of ancient samples in paleogenomics, to identify biomarkers for forensic reconstruction in evolutionary biology, and geolocalize samples.
PCA outcomes are used to shape study design, identify, and characterize individuals and populations, and draw historical and ethnobiological conclusions on origins, evolution, dispersion, and relatedness.
It is used to examine the population structure of a cohort or individuals to determine ancestry, analyze the demographic history and admixture, decide on the genetic similarity of samples and exclude outliers, decide how to model the populations in downstream analyses, describe the ancient and modern genetic relationships between the samples, infer kinship, identify ancestral clines in the data, e.g., Refs.16,17,18,19, detect genomic signatures of natural selection, e.g., Ref.20 and identify convergent evolution.
You can manipulate data any way you want within a black-box model. All such models, their code, logic, rules and their source data need to be reviewed by people who understand statistics, and IT system development. ‘Trusting’ the ‘science’ is naïve. Following the money is more likely to lead you to truth than ‘trusting’ black box sources with endless rhetoric and tautologies.