A review of applications of principles of quantum physics in oncology: do quantum physics principles have any role in oncology research and applications?
Bibliographic record
Abstract
Abstract Background: Research in the applications of the principles of quantum physics in oncology has progressed significantly over the past decades; and several research groups with professionals from diverse scientific background, including electrical engineers, mathematicians, biologists, atomic physicists, computer programmers, and biochemists, are working collaboratively in an unprecedented and pioneering economic, organisational and human effort searching for a wider and more effective, potentially definitive, understanding of the cancers. It is hypothesised that the principles of quantum physics could open new and broader understanding of the cancers and the development of new effective, targeted, accurate, personalised and possibly definitive cancer treatment. Materials and methods: This paper reports on a review of recent studies in the field of the applications of the principles of quantum physics in biology, chemistry, biochemistry and quantum physics in cancer research, including quantum physics principles and cancer, quantum modelling techniques, quantum dots and its applications in oncology, quantum cascade laser histopathology and quantum computing applications. Conclusions: The applications of the principles of quantum physics in oncology, chemistry and biology are providing new perspectives and greater insights into a long-studied disease, which could result in a greater understanding of the cancers and the potential for personalised and definitive treatment methods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".