Bibliographic record
Abstract
Overview Inheritance is associated with a paradox: it roars with the survival of the species, while at the same time it whispers a fragile message that is constantly modified even among kin. The genes, the environmental context and the traits that arise from their interaction are interrelated. A complexity that characterises this three-way relationship has been attributed to the nature–nurture dichotomy. Traditionally, nature is understood to mean the genes , whereas nurture denotes the environment . So, for example, people may debate why one pumpkin is superior to another – was it the quality of the soil or other growth conditions in the pumpkin patch, or was it the specific combination of alleles in that pumpkin's genome? In recent years, there has been a long-overdue paradigm shift from a limited focus on the nature–nurture dichotomy to a more expansive view that includes gene by environment (G × E) interactions and even gene–environment (G ↔ E) interdependencies, as defined and discussed in this chapter (Rutter 2007). A mechanistic basis for the concept of interdependency arose from advances in molecular biology and genomics which show that DNA is not only inherited but is also environmentally responsive. The latter argument is supported by findings that individuals with dissimilarities in their DNA (DNA polymorphisms) are differentially affected by the same environment. Different environments through development and adulthood can affect individuals with one genetic variant but not another.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".