Bibliographic record
Abstract
In 1940, as the Second World War escalated, 4-year-old Peter Grant was evacuated from London to a school in the English countryside on the Surrey–Hampshire border. Far from being traumatized by his sudden relocation, Grant, already a budding naturalist, remembers those years fondly. Peter Grant. “Our school was in the middle of fields with access to a little bit of forest,” he recalls. “I was just fascinated by the great big diversity of organisms that live in the outside world.” Safe from the destruction in London, Grant collected butterflies, watched birds, and identified flowers. This early experience helped shape his career in ecology and evolutionary biology, which has resulted in some remarkable accomplishments. Grant is now an emeritus professor and Class of 1877 Professor of Zoology at Princeton University (Princeton, NJ). He was elected to the National Academy of Sciences in 2007. Grant and his wife Rosemary, who was elected to the Academy in 2008, received the Kyoto Prize in Japan in December 2009. No strangers to international acclaim, the Grants are also members of the Royal Society of London, the Royal Society of Canada, and have won the Royal Society Darwin Medal, the Darwin-Wallace Medal of the Linnean Society, and the Balzan Foundation Prize. Grant’s Inaugural Article in the November 16, 2009 issue of PNAS details both the random and deterministic processes that can influence the development of a species (1). Grant and his wife observed the immigration in 1981 of a medium ground finch ( Geospiza fortis ) to Daphne Major, the small volcanic island in the Galapagos chain that has played host to much of the couple’s research. The lone bird was unusual in many respects; it sang an atypical song, was larger than similar birds, had a pointed, oversized beak, and contained alleles that marked it as 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.100 | 0.057 |
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".