Bibliographic record
Abstract
The thrifty phenotype hypothesis is widely used to interpret associations between early nutritional experience and degenerative disease risks. However, it remains unclear what is adaptive about early life thrift, and biomedical approaches struggle to explain why associations between early growth and later disease hold across the entire range of birth size. This issue can be addressed using a simple model, attributing disease to a high metabolic load (large tissue masses, rich diet, and sedentary lifestyle) relative to metabolic capacity (physiological traits contingent on fetal/infant development). In this context, different hypotheses regarding the long-term functions of thrift can be examined. The "predictive adaptive response" hypothesis considers thrift to involve metabolic adaptations (insulin resistance and central adiposity) that emerge in anticipation of a poor quality adult breeding environment. The competing "maternal capital" hypothesis considers thrift to involve reductions in lean mass and organ phenotype arising through constraints on maternal phenotype, reflecting both maternal developmental experience and current ecological conditions. This hypothesis assumes offspring developmental responses to stresses such as temperature, altitude, and nutritional ecology occur under the influence of maternal capital indices, including size, physiology, reproductive history and social status. I argue that insulin resistance only emerges after infancy, and far from being anticipatory of a low nutritional plane, indicates perturbations of metabolism. Following exposure of early thrifty growth to the obesogenic niche. Thrift as early growth variability represents a plausible profile of developmental plasticity for human evolutionary history, aiding understand how the modern obesogenic environment interacts with physiological variability to induce disease.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".