Bibliographic record
Abstract
See article by Lyngdorf et al. [10] (pages 854–862) in this issue. In less than 100 years, biology and medicine have been transformed by the effects of research that has eclipsed that of the 19th century in chemistry and that of the early half of the 20th century in physics. Whereas clinical research on human subjects has been important at the level of the application of knowledge at the bedside, the fundamental discoveries have been the result of basic science. Since the days of Harvey [1], real advances in the biomedical sciences have depended critically on the use of animals as models of human physiology, pathophysiology, and metabolism. Current animal models constitute technology that has been derived from scientific advances that, in turn, foster new scientific understanding and developments. The widespread use of rodent models dates from seminal work at the Wistar Institute where, starting in 1906, Donaldson [2] established the rat as a defined animal model for the study of many aspects of physiology. As he pointed out, the rat has many similarities to humans and its rapid development makes the study of life cycle processes practical. It is also both small enough to be inexpensive to breed and house and large enough to allow many studies of physiology and metabolism that are difficult or impossible in smaller species. The development of the mouse came somewhat later, led by work at the Jackson Laboratory, and benefited greatly from new techniques in genetics. The unraveling of the genetic code … *Tel.: +1-780-492-6359; fax: +1-780-492-1308.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.013 |
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".