Neuroquantum Theories of Psychiatric Genetics: Can Physical Forces Induce Epigenetic Influence on Future Genomes?
Bibliographic record
Abstract
This paper serves to encourage quantum physicists to engage in psychiatric based research on the brain and its functions (i.e. consciousness, memory, attention). By using physics theorems such as Einstein’s theory of relativity and the string theory, both physicists and geneticists alike may be able to elucidate potential links between components of the universe and their effects on the human brain. We have outlined some interesting posits including the cosmos’ role in evolutionary biology, alpha bonding in biological molecules, and environmentally induced epigenetic effects on genetics. We also explore how physical forces can influence human memory, behavioral traits, and rates of addiction. Impulsiveness is used to exemplify how environmental changes can contribute to epigenetics and its hereditary alterations. We propose the idea of the presence of a “mental universe,” where brain functionality like consciousness is a continuum of physically altered pathways. The realization that the universe and all of its precepts remains a mystery is reflected in the lack of a standardized “unified” physics theorem and mathematical equation that can explain universal dimensions (physical and mental), and as such, so is the complex nature of the functionality of the human brain. We provide herein a suggestion to remedy possible confusion, whereby we attempt to show the relationship of brain as a complex quantum–like organ and the impact of epigenetics on behavioral expression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".