The naked truth: a comprehensive clarification and classification of current ‘myths’ in naked mole‐rat biology
Bibliographic record
Abstract
The naked mole-rat (Heterocephalus glaber) has fascinated zoologists for at least half a century. It has also generated considerable biomedical interest not only because of its extraordinary longevity, but also because of unusual protective features (e.g. its tolerance of variable oxygen availability), which may be pertinent to several human disease states, including ischemia/reperfusion injury and neurodegeneration. A recent article entitled 'Surprisingly long survival of premature conclusions about naked mole-rat biology' described 28 'myths' which, those authors claimed, are a 'perpetuation of beautiful, but falsified, hypotheses' and impede our understanding of this enigmatic mammal. Here, we re-examine each of these 'myths' based on evidence published in the scientific literature. Following Braude et al., we argue that these 'myths' fall into four main categories: (i) 'myths' that would be better described as oversimplifications, some of which persist solely in the popular press; (ii) 'myths' that are based on incomplete understanding, where more evidence is clearly needed; (iii) 'myths' where the accumulation of evidence over the years has led to a revision in interpretation, but where there is no significant disagreement among scientists currently working in the field; (iv) 'myths' where there is a genuine difference in opinion among active researchers, based on alternative interpretations of the available evidence. The term 'myth' is particularly inappropriate when applied to competing, evidence-based hypotheses, which form part of the normal evolution of scientific knowledge. Here, we provide a comprehensive critical review of naked mole-rat biology and attempt to clarify some of these misconceptions.
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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 | 0.059 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.007 | 0.073 |
| Scholarly communication | 0.018 | 0.036 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.010 | 0.023 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".