Terrestrial Mammalian Predator/Prey Systems: Northern Hemisphere Ratios, Species Richness and Species Composition
Bibliographic record
Abstract
In the Neoarctic Biogeographic Region, Pre-Columbian terrestrial mammalian ecosystems were re-constructed to approximately 1400 AD* and terrestrial mammalian predator/prey species lists were developed for each macro-community in each biome. Faunal assemblages for the Palearctic Biogeographic Region were re-constructed to approximately 1000 AD and macro-communities associated with the various biomes ranged from Western Europe to eastern Siberia. From these data, it was concluded that: (1) terrestrial mammalian "species richness" increases from north to south in the northern hemisphere, (2) terrestrial mammalian "species composition" changes in all macrocommunities in all biomes and (3) the mean terrestrial mammalian predator/prey ratio remains constant approximating 0.75 in all macro-communities in all the biomes of the Neoarctic and Palearctic Biogeographic Regions and appears to be universal macro-ecological pattern throughout the entire Northern Hemisphere, (4) the evolution of optimal foraging strategies associated with a 0.75 predator/prey ratio represents the mean upper limit of specialization that terrestrial mammalian predators can attain in the northern hemisphere, where prey populations cycle and primary prey availability varies widely. Changes in macro-ecological patterns in the terrestrial mammalian predator/prey systems from the 0.75 ratio in the Northern Hemisphere have implications for conservation biology and wildlife management related to sustaining ecological equilibrium. ---- * Anno Dominu - наша эра
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".