Bibliographic record
Abstract
This short manuscript summarizes the framework developed by Tozzi and Peters in the years 2015-2017. We claim that the Borsuk-Ulam Theorem (BUT), is not simply a metaphor, rather a real computational tool standing for a universal principle for physical and biological systems. Indeed, the BUT perspective allows a feature (e.g., a shape, a trajectory or an energy) located in the environment to be translated to an abstract space and vice versa. Achieving a map from one system to another enables researchers to assess and elucidate a wide range of phenomena. We provided either demonstrations or testable hypotheses related to the BUT framework in far-flung disciplines, such as neuroscience, theoretical physics, nanomaterials, computational topology, applied algebraic topology, philosophy of the mind, chaotic systems, group theory and cosmology. We collaborated with foremost scientists from Canada, China, Czech Republic, Finland, France, Hungary, Iran, Italy, Norway, Poland, Russia, Slovenia, Spain, Sweden, Turkey, United Kingdom, U.S.A.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".