Review of mammalogical research in the Guianas of northern South America
Bibliographic record
Abstract
Research on mammals in the Guianas of northern South America has had a checkered history. In this review, I summarize the notable contributions to mammalogical study in Guyana, Suriname and French Guiana. These studies began in the mid-18th century with the binomial nomenclature system of scientific classification created by the Swedish naturalist Carl Linnaeus, who described 23 species new to science based on holotype specimens from the Guianas. Notwithstanding popular accounts by amateur naturalists visiting this region, over the next 7 decades there was only sporadic taxonomic work done on Guianan mammals primarily by researchers at European museums. The first comprehensive biological exploration took place in the 1840s during a geographic survey of the boundaries of British Guiana. However, it was not until almost half a century later that scientific publications began to regularly document the increasing species diversity in the region, including the prodigious work of Oldfield Thomas at the British Museum of Natural History in London. Another lull in the study of mammals occurred in the mid-1910s to the early 1960s after which foreign researchers began to rediscover the Guianas and their pristine habitats. This biological renaissance is still ongoing and I give a prospectus on the direction of future research in one of the last frontiers of tropical rainforest. An initiative that would be greatly beneficial is the establishment of a university network in the Guianas with graduate-based research to develop a cadre of professional experts on biodiversity and evolution as seen in other countries of South America.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".