Modelling skin disease: Lessons from the worlds of mathematics, physics and computer science
Bibliographic record
Abstract
Theoretical biology is a field that attempts to understand the complex phenomena of life in terms of mathematical and physical principles. Likewise, theoretical medicine employs mathematical arguments and models as a methodology in approaching the complexities of human disease. Naturally, these concepts can be applied to dermatology. There are many possible methods available in the theoretical investigation of skin disease. A number of examples are presented briefly. These include the mathematical modelling of pattern formation in congenital naevi and erythema gyratum repens, an information-theoretic approach to the analysis of genetic networks in autoimmunity, and computer simulations of early melanoma growth. To conclude, an analogy is drawn between the behaviour of well-known physical processes, such as earthquakes, and the spatio-temporal evolution of skin disease. Creating models in skin disease can lead to predictions that can be investigated experimentally or by observation and offer the prospect of unexpected or important insights into pathogenesis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".