Wallacean mammalogy and zooarchaeology: remembrances and a renaissance
Bibliographic record
Abstract
[Excerpt] The richness of life is not distributed haphazardly across the globe, but instead exhibits profound, non-random patterns. Numbers of species of insects, trees, and frogs, for example, abound in tropical localities, like in Brazil or the Congo, but not in Siberia or the Yukon. Species uniqueness, or endemism, peaks on large, long-isolated islands, like Madagascar or the Philippines. And different continents often have profoundly different assemblages of organisms. These types of observations regarding major patterns in the distribution of life, and their implied histories, formed the original foundation of the science of biogeography. Among the most important developers of this science was Alfred Russel Wallace, one of the architects of evolutionary biology. One of Wallace’s many fundamental biogeographic insights was the realization that the fauna of the “Malay Archipelago”, extending from the Malay Peninsula to New Guinea, much of which is now encompassed within the modern nation of Indonesia, can be demarcated into zones of marked Asian and Australian character. (This was an insight based on firsthand fieldwork, collecting biological specimens for museums.) These zones of regional influence merge and meld along the island chain, but nevertheless a particularly sharp demarcation runs between the islands of Borneo and Sulawesi in the north, and Bali and Lombok, in the south. This demarcation is now known as the “Wallace Line” (Wallace, 1869, 1876; Fig. 1), and others later built on these Wallacean insights to identify additional “lines” of biogeographic significance in the archipelago (Fig. 1). … Helgen, Kristofer M., and Rebecca K. Jones. 2023. Wallacean mammalogy and zooarchaeology: remembrances and a renaissance. In Contributions to Mammalogy and Zooarchaeology of Wallacea, ed. K. M. Helgen and R. K. Jones. Records of the Australian Museum 75(5): 623–628.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".