Optimizing our patient’s entropy production as therapy? Hypotheses originating from the physics of physiology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Physical laws dictate that energy is preserved; yet energy gradients irreversibly dissipate, thus producing entropy. As living complex non-equilibrium systems, humans must produce entropy continuously over time to create healthy internal emergent order. Entropy production is measured by heat production divided by temperature. Several hypotheses are presented. First, human entropy production is due to both metabolism and consciousness, dissipating energy and information gradients. Second, the physical drive for maximal entropy production is responsible for spontaneous formation of fractal multi-scale self-similar structures in time and space, ubiquitous and essential for health. Third, the evolutionary drive for enhanced function and adaptability selects states with both robust basal and maximal entropy production (i.e. the capacity to augment it when required). Last, targeted focus on optimizing our patients’ entropy production will improve health and clinical outcomes. These hypotheses have implications for understanding health, metabolism and consciousness, and offer novel clinical treatment strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it